Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
Data-Driven H∞ Control for Nonlinear Distributed Parameter Systems.
Luo, Biao; Huang, Tingwen; Wu, Huai-Ning; Yang, Xiong
2015-11-01
The data-driven H∞ control problem of nonlinear distributed parameter systems is considered in this paper. An off-policy learning method is developed to learn the H∞ control policy from real system data rather than the mathematical model. First, Karhunen-Loève decomposition is used to compute the empirical eigenfunctions, which are then employed to derive a reduced-order model (ROM) of slow subsystem based on the singular perturbation theory. The H∞ control problem is reformulated based on the ROM, which can be transformed to solve the Hamilton-Jacobi-Isaacs (HJI) equation, theoretically. To learn the solution of the HJI equation from real system data, a data-driven off-policy learning approach is proposed based on the simultaneous policy update algorithm and its convergence is proved. For implementation purpose, a neural network (NN)- based action-critic structure is developed, where a critic NN and two action NNs are employed to approximate the value function, control, and disturbance policies, respectively. Subsequently, a least-square NN weight-tuning rule is derived with the method of weighted residuals. Finally, the developed data-driven off-policy learning approach is applied to a nonlinear diffusion-reaction process, and the obtained results demonstrate its effectiveness.
Zhang, Ridong; Tao, Jili; Lu, Renquan; Jin, Qibing
2018-02-01
Modeling of distributed parameter systems is difficult because of their nonlinearity and infinite-dimensional characteristics. Based on principal component analysis (PCA), a hybrid modeling strategy that consists of a decoupled linear autoregressive exogenous (ARX) model and a nonlinear radial basis function (RBF) neural network model are proposed. The spatial-temporal output is first divided into a few dominant spatial basis functions and finite-dimensional temporal series by PCA. Then, a decoupled ARX model is designed to model the linear dynamics of the dominant modes of the time series. The nonlinear residual part is subsequently parameterized by RBFs, where genetic algorithm is utilized to optimize their hidden layer structure and the parameters. Finally, the nonlinear spatial-temporal dynamic system is obtained after the time/space reconstruction. Simulation results of a catalytic rod and a heat conduction equation demonstrate the effectiveness of the proposed strategy compared to several other methods.
Directory of Open Access Journals (Sweden)
Chengdong Yang
2015-01-01
Full Text Available This paper addresses the exponential synchronization problem of a class of master-slave distributed parameter systems (DPSs with spatially variable coefficients and spatiotemporally variable nonlinear perturbation, modeled by a couple of semilinear parabolic partial differential equations (PDEs. With a locally Lipschitz constraint, the perturbation is a continuous function of time, space, and system state. Firstly, a sufficient condition for the robust exponential synchronization of the unforced semilinear master-slave PDE systems is investigated for all admissible nonlinear perturbations. Secondly, a robust distributed proportional-spatial derivative (P-sD state feedback controller is desired such that the closed-loop master-slave PDE systems achieve exponential synchronization. Using Lyapunov’s direct method and the technique of integration by parts, the main results of this paper are presented in terms of spatial differential linear matrix inequalities (SDLMIs. Finally, two numerical examples are provided to show the effectiveness of the proposed methods applied to the robust exponential synchronization problem of master-slave PDE systems with nonlinear perturbation.
Distributed nonlinear optical response
DEFF Research Database (Denmark)
Nikolov, Nikola Ivanov
2005-01-01
of bound states of out of phase bright solitons and dark solitons. Also, the newly introduced analogy between the nonlocal cubic nonlinear and the quadratic nonlinear media, presented in paper B and Chapter 3 is discussed. In particular it supplies intuitive physical meaning of the formation of solitons...... in quadratic nonlinear media. In the second part of the report (Chapter 4), the possibility to obtain light with ultrabroad spectrum due to the interplay of many nonlinear effects based on cubic nonlinearity is investigated thoroughly. The contribution of stimulated Raman scattering, a delayed nonlinear...... a modified nonlinear Schroedinger model equation. Chapter 4 and papers D and E are dedicated to this part of the research....
Parameter Estimation of Nonlinear Models in Forestry.
Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.
1999-01-01
Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...
Describing pediatric dysphonia with nonlinear dynamic parameters
Meredith, Morgan L.; Theis, Shannon M.; McMurray, J. Scott; Zhang, Yu; Jiang, Jack J.
2008-01-01
Objective Nonlinear dynamic analysis has emerged as a reliable and objective tool for assessing voice disorders. However, it has only been tested on adult populations. In the present study, nonlinear dynamic analysis was applied to normal and dysphonic pediatric populations with the goal of collecting normative data. Jitter analysis was also applied in order to compare nonlinear dynamic and perturbation measures. This study’s findings will be useful in creating standards for the use of nonlinear dynamic analysis as a tool to describe dysphonia in the pediatric population. Methods The study included 38 pediatric subjects (23 children with dysphonia and 15 without). Recordings of sustained vowels were obtained from each subject and underwent nonlinear dynamic analysis and percent jitter analysis. The resulting correlation dimension (D2) and percent jitter values were compared across the two groups using t-tests set at a significance level of p = 0.05. Results It was shown that D2 values covary with the presence of pathology in children. D2 values were significantly higher in dysphonic children than in normal children (p = 0.002). Standard deviations indicated a higher level of variation in normal children’s D2 values than in dysphonic children’s D2 values. Jitter analysis showed markedly higher percent jitter in dysphonic children than in normal children (p = 0.025) and large standard deviations for both groups. Conclusion This study indicates that nonlinear dynamic analysis could be a viable tool for the detection and assessment of dysphonia in children. Further investigations and more normative data are needed to create standards for using nonlinear dynamic parameters for the clinical evaluation of pediatric dysphonia. PMID:18947887
Distributed Parameter Modelling Applications
DEFF Research Database (Denmark)
Sales-Cruz, Mauricio; Cameron, Ian; Gani, Rafiqul
2011-01-01
and the development of a short-path evaporator. The oil shale processing problem illustrates the interplay amongst particle flows in rotating drums, heat and mass transfer between solid and gas phases. The industrial application considers the dynamics of an Alberta-Taciuk processor, commonly used in shale oil and oil...... the steady state, distributed behaviour of a short-path evaporator....
SYVAC3 parameter distribution package
Energy Technology Data Exchange (ETDEWEB)
Andres, T; Skeet, A
1995-01-01
SYVAC3 (Systems Variability Analysis Code, generation 3) is a computer program that implements a method called systems variability analysis to analyze the behaviour of a system in the presence of uncertainty. This method is based on simulating the system many times to determine the variation in behaviour it can exhibit. SYVAC3 specializes in systems representing the transport of contaminants, and has several features to simplify the modelling of such systems. It provides a general tool for estimating environmental impacts from the dispersal of contaminants. This report describes a software object type (a generalization of a data type) called Parameter Distribution. This object type is used in SYVAC3, and can also be used independently. Parameter Distribution has the following subtypes: beta distribution; binomial distribution; constant distribution; lognormal distribution; loguniform distribution; normal distribution; piecewise uniform distribution; Triangular distribution; and uniform distribution. Some of these distributions can be altered by correlating two parameter distribution objects. This report provides complete specifications for parameter distributions, and also explains how to use them. It should meet the needs of casual users, reviewers, and programmers who wish to add their own subtypes. (author). 30 refs., 75 tabs., 56 figs.
varying elastic parameters distributions
Moussawi, Ali
2014-12-01
The experimental identication of mechanical properties is crucial in mechanics for understanding material behavior and for the development of numerical models. Classical identi cation procedures employ standard shaped specimens, assume that the mechanical elds in the object are homogeneous, and recover global properties. Thus, multiple tests are required for full characterization of a heterogeneous object, leading to a time consuming and costly process. The development of non-contact, full- eld measurement techniques from which complex kinematic elds can be recorded has opened the door to a new way of thinking. From the identi cation point of view, suitable methods can be used to process these complex kinematic elds in order to recover multiple spatially varying parameters through one test or a few tests. The requirement is the development of identi cation techniques that can process these complex experimental data. This thesis introduces a novel identi cation technique called the constitutive compatibility method. The key idea is to de ne stresses as compatible with the observed kinematic eld through the chosen class of constitutive equation, making possible the uncoupling of the identi cation of stress from the identi cation of the material parameters. This uncoupling leads to parametrized solutions in cases where 5 the solution is non-unique (due to unknown traction boundary conditions) as demonstrated on 2D numerical examples. First the theory is outlined and the method is demonstrated in 2D applications. Second, the method is implemented within a domain decomposition framework in order to reduce the cost for processing very large problems. Finally, it is extended to 3D numerical examples. Promising results are shown for 2D and 3D problems.
Optimization of nonlinear wave function parameters
International Nuclear Information System (INIS)
Shepard, R.; Minkoff, M.; Chemistry
2006-01-01
An energy-based optimization method is presented for our recently developed nonlinear wave function expansion form for electronic wave functions. This expansion form is based on spin eigenfunctions, using the graphical unitary group approach (GUGA). The wave function is expanded in a basis of product functions, allowing application to closed-shell and open-shell systems and to ground and excited electronic states. Each product basis function is itself a multiconfigurational function that depends on a relatively small number of nonlinear parameters called arc factors. The energy-based optimization is formulated in terms of analytic arc factor gradients and orbital-level Hamiltonian matrices that correspond to a specific kind of uncontraction of each of the product basis functions. These orbital-level Hamiltonian matrices give an intuitive representation of the energy in terms of disjoint subsets of the arc factors, they provide for an efficient computation of gradients of the energy with respect to the arc factors, and they allow optimal arc factors to be determined in closed form for subspaces of the full variation problem. Timings for energy and arc factor gradient computations involving expansion spaces of > 10 24 configuration state functions are reported. Preliminary convergence studies and molecular dissociation curves are presented for some small molecules
Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor
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Lin Ye
2014-02-01
Full Text Available Using the finite element method (FEM and particle swarm optimization (PSO, a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters’ effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°.
NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION
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Roman L. Leibov
2017-09-01
Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented
Parameter estimation and prediction of nonlinear biological systems: some examples
Doeswijk, T.G.; Keesman, K.J.
2006-01-01
Rearranging and reparameterizing a discrete-time nonlinear model with polynomial quotient structure in input, output and parameters (xk = f(Z, p)) leads to a model linear in its (new) parameters. As a result, the parameter estimation problem becomes a so-called errors-in-variables problem for which
A Novel Nonlinear Parameter Estimation Method of Soft Tissues
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Qianqian Tong
2017-12-01
Full Text Available The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values. To provide highly precise data for estimating nonlinear parameters, the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine (WCFM_SVM. Secondly, a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues, using the substitution parameters of Young’s modulus and Poisson’s ratio to avoid solving complicated nonlinear problems. To improve the robustness of our model and avoid poor local minima, the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally, a self-adapting Levenberg–Marquardt (LM algorithm was presented, which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM_SVM model was less than 0.03 Newton, resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm, demonstrating that our nonlinear parameters are precise.
Riccati-parameter solutions of nonlinear second-order ODEs
International Nuclear Information System (INIS)
Reyes, M A; Rosu, H C
2008-01-01
It has been proven by Rosu and Cornejo-Perez (Rosu and Cornejo-Perez 2005 Phys. Rev. E 71 046607, Cornejo-Perez and Rosu 2005 Prog. Theor. Phys. 114 533) that for some nonlinear second-order ODEs it is a very simple task to find one particular solution once the nonlinear equation is factorized with the use of two first-order differential operators. Here, it is shown that an interesting class of parametric solutions is easy to obtain if the proposed factorization has a particular form, which happily turns out to be the case in many problems of physical interest. The method that we exemplify with a few explicitly solved cases consists in using the general solution of the Riccati equation, which contributes with one parameter to this class of parametric solutions. For these nonlinear cases, the Riccati parameter serves as a 'growth' parameter from the trivial null solution up to the particular solution found through the factorization procedure
Ndoye, Ibrahima; Voos, Holger; Laleg-Kirati, Taous-Meriem; Darouach, Mohamed
2014-01-01
In this paper, an adaptive observer design with parameter identification for a nonlinear system with external perturbations and unknown parameters is proposed. The states of the nonlinear system are estimated by a nonlinear observer and the unknown
Nonlinear Progressive Collapse Analysis Including Distributed Plasticity
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Mohamed Osama Ahmed
2016-01-01
Full Text Available This paper demonstrates the effect of incorporating distributed plasticity in nonlinear analytical models used to assess the potential for progressive collapse of steel framed regular building structures. Emphasis on this paper is on the deformation response under the notionally removed column, in a typical Alternate Path (AP method. The AP method employed in this paper is based on the provisions of the Unified Facilities Criteria – Design of Buildings to Resist Progressive Collapse, developed and updated by the U.S. Department of Defense [1]. The AP method is often used for to assess the potential for progressive collapse of building structures that fall under Occupancy Category III or IV. A case study steel building is used to examine the effect of incorporating distributed plasticity, where moment frames were used on perimeter as well as the interior of the three dimensional structural system. It is concluded that the use of moment resisting frames within the structural system will enhance resistance to progressive collapse through ductile deformation response and that it is conserative to ignore the effects of distributed plasticity in determining peak displacement response under the notionally removed column.
Estimation of Physical Parameters in Linear and Nonlinear Dynamic Systems
DEFF Research Database (Denmark)
Knudsen, Morten
variance and confidence ellipsoid is demonstrated. The relation is based on a new theorem on maxima of an ellipsoid. The procedure for input signal design and physical parameter estimation is tested on a number of examples, linear as well as nonlinear and simulated as well as real processes, and it appears...
Measurement of the Acoustic Nonlinearity Parameter for Biological Media.
Cobb, Wesley Nelson
In vitro measurements of the acoustic nonlinearity parameter are presented for several biological media. With these measurements it is possible to predict the distortion of a finite amplitude wave in biological tissues of current diagnostic and research interest. The measurement method is based on the finite amplitude distortion of a sine wave that is emmitted by a piston source. The growth of the second harmonic component of this wave is measured by a piston receiver which is coaxial with and has the same size as the source. The experimental measurements and theory are compared in order to determine the nonlinearity parameter. The density, sound speed, and attenuation for the medium are determined in order to make this comparison. The theory developed for this study accounts for the influence of both diffraction and attenuation on the experimental measurements. The effects of dispersion, tissue inhomogeneity and gas bubbles within the excised tissues are studied. To test the measurement method, experimental results are compared with established values for the nonlinearity parameter of distilled water, ethylene glycol and glycerol. The agreement between these values suggests that the measurement uncertainty is (+OR-) 5% for liquids and (+OR-) 10% for solid tissues. Measurements are presented for dog blood and bovine serum albumen as a function of concentration. The nonlinearity parameters for liver, kidney and spleen are reported for both human and canine tissues. The values for the fresh tissues displayed little variation (6.8 to 7.8). Measurements for fixed, normal and cirrhotic tissues indicated that the nonlinearity parameter does not depend strongly on pathology. However, the values for fixed tissues were somewhat higher than those of the fresh tissues.
Recovering Parameters of Johnson's SB Distribution
Bernard R. Parresol
2003-01-01
A new parameter recovery model for Johnson's SB distribution is developed. This latest alternative approach permits recovery of the range and both shape parameters. Previous models recovered only the two shape parameters. Also, a simple procedure for estimating the distribution minimum from sample values is presented. The new methodology...
Weyl geometry and the nonlinear mechanics of distributed point defects
Yavari, A.; Goriely, A.
2012-01-01
The residual stress field of a nonlinear elastic solid with a spherically symmetric distribution of point defects is obtained explicitly using methods from differential geometry. The material manifold of a solid with distributed point defects
Ripple distribution for nonlinear fiber-optic channels.
Sorokina, Mariia; Sygletos, Stylianos; Turitsyn, Sergei
2017-02-06
We demonstrate data rates above the threshold imposed by nonlinearity on conventional optical signals by applying novel probability distribution, which we call ripple distribution, adapted to the properties of the fiber channel. Our results offer a new direction for signal coding, modulation and practical nonlinear distortions compensation algorithms.
Distributed Synchronization Control of Multiagent Systems With Unknown Nonlinearities.
Su, Shize; Lin, Zongli; Garcia, Alfredo
2016-01-01
This paper revisits the distributed adaptive control problem for synchronization of multiagent systems where the dynamics of the agents are nonlinear, nonidentical, unknown, and subject to external disturbances. Two communication topologies, represented, respectively, by a fixed strongly-connected directed graph and by a switching connected undirected graph, are considered. Under both of these communication topologies, we use distributed neural networks to approximate the uncertain dynamics. Decentralized adaptive control protocols are then constructed to solve the cooperative tracker problem, the problem of synchronization of all follower agents to a leader agent. In particular, we show that, under the proposed decentralized control protocols, the synchronization errors are ultimately bounded, and their ultimate bounds can be reduced arbitrarily by choosing the control parameter appropriately. Simulation study verifies the effectiveness of our proposed protocols.
Parameter and state estimation in nonlinear dynamical systems
Creveling, Daniel R.
This thesis is concerned with the problem of state and parameter estimation in nonlinear systems. The need to evaluate unknown parameters in models of nonlinear physical, biophysical and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. When verifying and validating these models, it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, this thesis develops a framework for presenting data to a candidate model of a physical process in a way that makes efficient use of the measured data while allowing for estimation of the unknown parameters in the model. The approach presented here builds on existing work that uses synchronization as a tool for parameter estimation. Some critical issues of stability in that work are addressed and a practical framework is developed for overcoming these difficulties. The central issue is the choice of coupling strength between the model and data. If the coupling is too strong, the model will reproduce the measured data regardless of the adequacy of the model or correctness of the parameters. If the coupling is too weak, nonlinearities in the dynamics could lead to complex dynamics rendering any cost function comparing the model to the data inadequate for the determination of model parameters. Two methods are introduced which seek to balance the need for coupling with the desire to allow the model to evolve in its natural manner without coupling. One method, 'balanced' synchronization, adds to the synchronization cost function a requirement that the conditional Lyapunov exponents of the model system, conditioned on being driven by the data, remain negative but small in magnitude. Another method allows the coupling between the data and the model to vary in time according to a specific form of differential equation. The coupling dynamics is damped to allow for a tendency toward zero coupling
Parameter identification in a nonlinear nuclear reactor model using quasilinearization
International Nuclear Information System (INIS)
Barreto, J.M.; Martins Neto, A.F.; Tanomaru, N.
1980-09-01
Parameter identification in a nonlinear, lumped parameter, nuclear reactor model is carried out using discrete output power measurements during the transient caused by an external reactivity change. In order to minimize the difference between the model and the reactor power responses, the parameter promt neutron generation time and a parameter in fuel temperature reactivity coefficient equation are adjusted using quasilinearization. The influences of the external reactivity disturbance, the number and frequency of measurements and the measurement noise level on the method accuracy and rate of convergence are analysed through simulation. Procedures for the design of the identification experiments are suggested. The method proved to be very effective for low level noise measurements. (Author) [pt
Parameter Identification for Nonlinear Circuit Models of Power BAW Resonator
Directory of Open Access Journals (Sweden)
CONSTANTINESCU, F.
2011-02-01
Full Text Available The large signal operation of the bulk acoustic wave (BAW resonators is characterized by the amplitude-frequency effect and the intermodulation effect. The measurement of these effects, together with that of the small signal frequency characteristic, are used in this paper for the parameter identification of the nonlinear circuit models developed previously by authors. As the resonator has been connected to the measurement bench by wire bonding, the parasitic elements of this connection have been taken into account, being estimated solving some electrical and magnetic field problems.
Variation of nonlinearity parameter at low fundamental amplitudes
Barnard, Daniel J.
1999-04-01
Recent harmonic generation measurements of the nonlinearity parameter β in polycrystalline Cu-Al alloys have shown a transition to lower values at low fundamental amplitude levels. Values for β at high (>10 Å) fundamental levels are in the range predicted by single-crystal second- and third-order elastic constants while lower fundamental levels (alloy by others. The source of the effect is unclear but initial results may require a reexamination of current methods for measurement of third-order elastic constants.
A numerical study of non-linear crack tip parameters
Directory of Open Access Journals (Sweden)
F.V. Antunes
2015-07-01
Full Text Available Crack closure concept has been widely used to explain different issues of fatigue crack propagation. However, different authors have questioned the relevance of crack closure and have proposed alternative concepts. The main objective here is to check the effectiveness of crack closure concept by linking the contact of crack flanks with non-linear crack tip parameters. Accordingly, 3D-FE numerical models with and without contact were developed for a wide range of loading scenarios and the crack tip parameters usually linked to fatigue crack growth, namely range of cyclic plastic strain, crack tip opening displacement, size of reversed plastic zone and total plastic dissipation per cycle, were investigated. It was demonstrated that: i LEFM concepts are applicable to the problem under study; ii the crack closure phenomenon has a great influence on crack tip parameters decreasing their values; iii the Keff concept is able to explain the variations of crack tip parameters produced by the contact of crack flanks; iv the analysis of remote compliance is the best numerical parameter to quantify the crack opening level; v without contact there is no effect of stress ratio on crack tip parameters. Therefore it is proved that the crack closure concept is valid.
Distributed Fault Detection for a Class of Nonlinear Stochastic Systems
Directory of Open Access Journals (Sweden)
Bingyong Yan
2014-01-01
Full Text Available A novel distributed fault detection strategy for a class of nonlinear stochastic systems is presented. Different from the existing design procedures for fault detection, a novel fault detection observer, which consists of a nonlinear fault detection filter and a consensus filter, is proposed to detect the nonlinear stochastic systems faults. Firstly, the outputs of the nonlinear stochastic systems act as inputs of a consensus filter. Secondly, a nonlinear fault detection filter is constructed to provide estimation of unmeasurable system states and residual signals using outputs of the consensus filter. Stability analysis of the consensus filter is rigorously investigated. Meanwhile, the design procedures of the nonlinear fault detection filter are given in terms of linear matrix inequalities (LMIs. Taking the influence of the system stochastic noises into consideration, an outstanding feature of the proposed scheme is that false alarms can be reduced dramatically. Finally, simulation results are provided to show the feasibility and effectiveness of the proposed fault detection approach.
ESTIMATION ACCURACY OF EXPONENTIAL DISTRIBUTION PARAMETERS
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muhammad zahid rashid
2011-04-01
Full Text Available The exponential distribution is commonly used to model the behavior of units that have a constant failure rate. The two-parameter exponential distribution provides a simple but nevertheless useful model for the analysis of lifetimes, especially when investigating reliability of technical equipment.This paper is concerned with estimation of parameters of the two parameter (location and scale exponential distribution. We used the least squares method (LSM, relative least squares method (RELS, ridge regression method (RR, moment estimators (ME, modified moment estimators (MME, maximum likelihood estimators (MLE and modified maximum likelihood estimators (MMLE. We used the mean square error MSE, and total deviation TD, as measurement for the comparison between these methods. We determined the best method for estimation using different values for the parameters and different sample sizes
Linear parameter varying representations for nonlinear control design
Carter, Lance Huntington
Linear parameter varying (LPV) systems are investigated as a framework for gain-scheduled control design and optimal hybrid control. An LPV system is defined as a linear system whose dynamics depend upon an a priori unknown but measurable exogenous parameter. A gain-scheduled autopilot design is presented for a bank-to-turn (BTT) missile. The method is novel in that the gain-scheduled design does not involve linearizations about operating points. Instead, the missile dynamics are brought to LPV form via a state transformation. This idea is applied to the design of a coupled longitudinal/lateral BTT missile autopilot. The pitch and yaw/roll dynamics are separately transformed to LPV form, where the cross axis states are treated as "exogenous" parameters. These are actually endogenous variables, so such a plant is called "quasi-LPV." Once in quasi-LPV form, a family of robust controllers using mu synthesis is designed for both the pitch and yaw/roll channels, using angle-of-attack and roll rate as the scheduling variables. The closed-loop time response is simulated using the original nonlinear model and also using perturbed aerodynamic coefficients. Modeling and control of engine idle speed is investigated using LPV methods. It is shown how generalized discrete nonlinear systems may be transformed into quasi-LPV form. A discrete nonlinear engine model is developed and expressed in quasi-LPV form with engine speed as the scheduling variable. An example control design is presented using linear quadratic methods. Simulations are shown comparing the LPV based controller performance to that using PID control. LPV representations are also shown to provide a setting for hybrid systems. A hybrid system is characterized by control inputs consisting of both analog signals and discrete actions. A solution is derived for the optimal control of hybrid systems with generalized cost functions. This is shown to be computationally intensive, so a suboptimal strategy is proposed that
Parameter estimation in nonlinear models for pesticide degradation
International Nuclear Information System (INIS)
Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.
1991-01-01
A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)
Parameter Estimation and Prediction of a Nonlinear Storage Model: an algebraic approach
Doeswijk, T.G.; Keesman, K.J.
2005-01-01
Generally, parameters that are nonlinear in system models are estimated by nonlinear least-squares optimization algorithms. In this paper, if a nonlinear discrete-time model with a polynomial quotient structure in input, output, and parameters, a method is proposed to re-parameterize the model such
Bayesian estimation of Weibull distribution parameters
International Nuclear Information System (INIS)
Bacha, M.; Celeux, G.; Idee, E.; Lannoy, A.; Vasseur, D.
1994-11-01
In this paper, we expose SEM (Stochastic Expectation Maximization) and WLB-SIR (Weighted Likelihood Bootstrap - Sampling Importance Re-sampling) methods which are used to estimate Weibull distribution parameters when data are very censored. The second method is based on Bayesian inference and allow to take into account available prior informations on parameters. An application of this method, with real data provided by nuclear power plants operation feedback analysis has been realized. (authors). 8 refs., 2 figs., 2 tabs
Statistical distributions applications and parameter estimates
Thomopoulos, Nick T
2017-01-01
This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability. Understanding statistical distributions is fundamental for researchers in almost all disciplines. The informed researcher will select the statistical distribution that best fits the data in the study at hand. Some of the distributions are well known to the general researcher and are in use in a wide variety of ways. Other useful distributions are less understood and are not in common use. The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study. The distributions are for continuous, discrete, and bivariate random variables. In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values. In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of ...
Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.
Duffull, Stephen B; Hooker, Andrew C
2017-12-01
Optimal designs for nonlinear models are dependent on the choice of parameter values. Various methods have been proposed to provide designs that are robust to uncertainty in the prior choice of parameter values. These methods are generally based on estimating the expectation of the determinant (or a transformation of the determinant) of the information matrix over the prior distribution of the parameter values. For high dimensional models this can be computationally challenging. For nonlinear mixed-effects models the question arises as to the importance of accounting for uncertainty in the prior value of the variances of the random effects parameters. In this work we explore the influence of the variance of the random effects parameters on the optimal design. We find that the method for approximating the expectation and variance of the likelihood is of potential importance for considering the influence of random effects. The most common approximation to the likelihood, based on a first-order Taylor series approximation, yields designs that are relatively insensitive to the prior value of the variance of the random effects parameters and under these conditions it appears to be sufficient to consider uncertainty on the fixed-effects parameters only.
Boundary feedback stabilization of distributed parameter systems
DEFF Research Database (Denmark)
Pedersen, Michael
1988-01-01
The author introduces the method of pseudo-differential stabilization. He notes that the theory of pseudo-differential boundary operators is a fruitful approach to problems arising in control and stabilization theory of distributed-parameter systems. The basic pseudo-differential calculus can...
Parameter Scaling in Non-Linear Microwave Tomography
DEFF Research Database (Denmark)
Jensen, Peter Damsgaard; Rubæk, Tonny; Talcoth, Oskar
2012-01-01
Non-linear microwave tomographic imaging of the breast is a challenging computational problem. The breast is heterogeneous and contains several high-contrast and lossy regions, resulting in large differences in the measured signal levels. This implies that special care must be taken when the imag......Non-linear microwave tomographic imaging of the breast is a challenging computational problem. The breast is heterogeneous and contains several high-contrast and lossy regions, resulting in large differences in the measured signal levels. This implies that special care must be taken when...... the imaging problem is formulated. Under such conditions, microwave imaging systems will most often be considerably more sensitive to changes in the electromagnetic properties in certain regions of the breast. The result is that the parameters might not be reconstructed correctly in the less sensitive regions...... introduced as a measure of the sensitivity. The scaling of the parameters is shown to improve performance of the microwave imaging system when applied to reconstruction of images from 2-D simulated data and measurement data....
Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.
Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua
2016-11-14
In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.
Robust receding horizon control for networked and distributed nonlinear systems
Li, Huiping
2017-01-01
This book offers a comprehensive, easy-to-understand overview of receding-horizon control for nonlinear networks. It presents novel general strategies that can simultaneously handle general nonlinear dynamics, system constraints, and disturbances arising in networked and large-scale systems and which can be widely applied. These receding-horizon-control-based strategies can achieve sub-optimal control performance while ensuring closed-loop stability: a feature attractive to engineers. The authors address the problems of networked and distributed control step-by-step, gradually increasing the level of challenge presented. The book first introduces the state-feedback control problems of nonlinear networked systems and then studies output feedback control problems. For large-scale nonlinear systems, disturbance is considered first, then communication delay separately, and lastly the simultaneous combination of delays and disturbances. Each chapter of this easy-to-follow book not only proposes and analyzes novel ...
Distributed Extreme Learning Machine for Nonlinear Learning over Network
Directory of Open Access Journals (Sweden)
Songyan Huang
2015-02-01
Full Text Available Distributed data collection and analysis over a network are ubiquitous, especially over a wireless sensor network (WSN. To our knowledge, the data model used in most of the distributed algorithms is linear. However, in real applications, the linearity of systems is not always guaranteed. In nonlinear cases, the single hidden layer feedforward neural network (SLFN with radial basis function (RBF hidden neurons has the ability to approximate any continuous functions and, thus, may be used as the nonlinear learning system. However, confined by the communication cost, using the distributed version of the conventional algorithms to train the neural network directly is usually prohibited. Fortunately, based on the theorems provided in the extreme learning machine (ELM literature, we only need to compute the output weights of the SLFN. Computing the output weights itself is a linear learning problem, although the input-output mapping of the overall SLFN is still nonlinear. Using the distributed algorithmto cooperatively compute the output weights of the SLFN, we obtain a distributed extreme learning machine (dELM for nonlinear learning in this paper. This dELM is applied to the regression problem and classification problem to demonstrate its effectiveness and advantages.
Weyl geometry and the nonlinear mechanics of distributed point defects
Yavari, A.
2012-09-05
The residual stress field of a nonlinear elastic solid with a spherically symmetric distribution of point defects is obtained explicitly using methods from differential geometry. The material manifold of a solid with distributed point defects-where the body is stress-free-is a flat Weyl manifold, i.e. a manifold with an affine connection that has non-metricity with vanishing traceless part, but both its torsion and curvature tensors vanish. Given a spherically symmetric point defect distribution, we construct its Weyl material manifold using the method of Cartan\\'s moving frames. Having the material manifold, the anelasticity problem is transformed to a nonlinear elasticity problem and reduces the problem of computing the residual stresses to finding an embedding into the Euclidean ambient space. In the case of incompressible neo-Hookean solids, we calculate explicitly this residual stress field. We consider the example of a finite ball and a point defect distribution uniform in a smaller ball and vanishing elsewhere. We show that the residual stress field inside the smaller ball is uniform and hydrostatic. We also prove a nonlinear analogue of Eshelby\\'s celebrated inclusion problem for a spherical inclusion in an isotropic incompressible nonlinear solid. © 2012 The Royal Society.
Relative controllability of nonlinear neutral systems with distributed ...
African Journals Online (AJOL)
In this paper we study the relative controllability of nonlinear neutral system with distributed and multiple lumped time varying delays in control. Using Schauder's fixed point theorem sufficient conditions for relative controllability in a given time interval are formulated and proved. Journal of the Nigerian Association of ...
Photon nonlinear mixing in subcarrier multiplexed quantum key distribution systems.
Capmany, José
2009-04-13
We provide, for the first time to our knowledge, an analysis of the influence of nonlinear photon mixing on the end to end quantum bit error rate (QBER) performance of subcarrier multiplexed quantum key distribution systems. The results show that negligible impact is to be expected for modulation indexes in the range of 2%.
Evaluation of third order nonlinear optical parameters of CdS/PVA nanocomposite
International Nuclear Information System (INIS)
Sharma, Mamta; Tripathi, S. K.
2015-01-01
CdS nanoparticles dispersed in PVA are prepared by Chemical method at room temperature. The nonlinear optical parameters such as nonlinear absorption (β), nonlinear refractive index (n 2 ) and nonlinear susceptibility (χ 3 ) are calculated for this sample by using Z-scan technique. CdS/PVA samples show the two photon absorption mechanism. The third order nonlinear susceptibility is calculated from n 2 and β and is found to be of the order of 10 −7 – 10 −8 m 2 /V 2 . The larger value of third order nonlinear susceptibility is due to dielectric and quantum confinement effect
Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver
Kang, Ling; Zhou, Liwei
2018-02-01
Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.
Distribution Development for STORM Ingestion Input Parameters
Energy Technology Data Exchange (ETDEWEB)
Fulton, John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-07-01
The Sandia-developed Transport of Radioactive Materials (STORM) code suite is used as part of the Radioisotope Power System Launch Safety (RPSLS) program to perform statistical modeling of the consequences due to release of radioactive material given a launch accident. As part of this modeling, STORM samples input parameters from probability distributions with some parameters treated as constants. This report described the work done to convert four of these constant inputs (Consumption Rate, Average Crop Yield, Cropland to Landuse Database Ratio, and Crop Uptake Factor) to sampled values. Consumption rate changed from a constant value of 557.68 kg / yr to a normal distribution with a mean of 102.96 kg / yr and a standard deviation of 2.65 kg / yr. Meanwhile, Average Crop Yield changed from a constant value of 3.783 kg edible / m ^{2} to a normal distribution with a mean of 3.23 kg edible / m ^{2} and a standard deviation of 0.442 kg edible / m ^{2} . The Cropland to Landuse Database ratio changed from a constant value of 0.0996 (9.96%) to a normal distribution with a mean value of 0.0312 (3.12%) and a standard deviation of 0.00292 (0.29%). Finally the crop uptake factor changed from a constant value of 6.37e^{-4} (Bq crop /kg)/(Bq soil /kg) to a lognormal distribution with a geometric mean value of 3.38e^{-4} (Bq crop /kg)/(Bq soil /kg) and a standard deviation value of 3.33 (Bq crop /kg)/(Bq soil /kg)
Assigning probability distributions to input parameters of performance assessment models
Energy Technology Data Exchange (ETDEWEB)
Mishra, Srikanta [INTERA Inc., Austin, TX (United States)
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.
Assigning probability distributions to input parameters of performance assessment models
International Nuclear Information System (INIS)
Mishra, Srikanta
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available
Identification of systems with distributed parameters
International Nuclear Information System (INIS)
Moret, J.M.
1990-10-01
The problem of finding a model for the dynamical response of a system with distributed parameters based on measured data is addressed. First a mathematical formalism is developed in order to obtain the specific properties of such a system. Then a linear iterative identification algorithm is proposed that includes these properties, and that produces better results than usual non linear minimisation techniques. This algorithm is further improved by an original data decimation that allow to artificially increase the sampling period without losing between sample information. These algorithms are tested with real laboratory data
Shah, A A; Xing, W W; Triantafyllidis, V
2017-04-01
In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.
Reliability parameters of distribution networks components
Energy Technology Data Exchange (ETDEWEB)
Gono, R.; Kratky, M.; Rusek, S.; Kral, V. [Technical Univ. of Ostrava (Czech Republic)
2009-03-11
This paper presented a framework for the retrieval of parameters from various heterogenous power system databases. The framework was designed to transform the heterogenous outage data in a common relational scheme. The framework was used to retrieve outage data parameters from the Czech and Slovak republics in order to demonstrate the scalability of the framework. A reliability computation of the system was computed in 2 phases representing the retrieval of component reliability parameters and the reliability computation. Reliability rates were determined using component reliability and global reliability indices. Input data for the reliability was retrieved from data on equipment operating under similar conditions, while the probability of failure-free operations was evaluated by determining component status. Anomalies in distribution outage data were described as scheme, attribute, and term differences. Input types consisted of input relations; transformation programs; codebooks; and translation tables. The system was used to successfully retrieve data from 7 distributors in the Czech Republic and Slovak Republic between 2000-2007. The database included 301,555 records. Data were queried using SQL language. 29 refs., 2 tabs., 2 figs.
Ndoye, Ibrahima
2014-12-01
In this paper, an adaptive observer design with parameter identification for a nonlinear system with external perturbations and unknown parameters is proposed. The states of the nonlinear system are estimated by a nonlinear observer and the unknown parameters are also adapted to their values. Sufficient conditions for the stability of the adaptive observer error dynamics are derived in terms of linear matrix inequalities. Simulation results for chaotic Lorenz systems with unknown parameters in the presence of external perturbations are given to illustrate the effectiveness of our proposed approach. © 2014 IEEE.
Fukuda, J.; Johnson, K. M.
2009-12-01
Studies utilizing inversions of geodetic data for the spatial distribution of coseismic slip on faults typically present the result as a single fault plane and slip distribution. Commonly the geometry of the fault plane is assumed to be known a priori and the data are inverted for slip. However, sometimes there is not strong a priori information on the geometry of the fault that produced the earthquake and the data is not always strong enough to completely resolve the fault geometry. We develop a method to solve for the full posterior probability distribution of fault slip and fault geometry parameters in a Bayesian framework using Monte Carlo methods. The slip inversion problem is particularly challenging because it often involves multiple data sets with unknown relative weights (e.g. InSAR, GPS), model parameters that are related linearly (slip) and nonlinearly (fault geometry) through the theoretical model to surface observations, prior information on model parameters, and a regularization prior to stabilize the inversion. We present the theoretical framework and solution method for a Bayesian inversion that can handle all of these aspects of the problem. The method handles the mixed linear/nonlinear nature of the problem through combination of both analytical least-squares solutions and Monte Carlo methods. We first illustrate and validate the inversion scheme using synthetic data sets. We then apply the method to inversion of geodetic data from the 2003 M6.6 San Simeon, California earthquake. We show that the uncertainty in strike and dip of the fault plane is over 20 degrees. We characterize the uncertainty in the slip estimate with a volume around the mean fault solution in which the slip most likely occurred. Slip likely occurred somewhere in a volume that extends 5-10 km in either direction normal to the fault plane. We implement slip inversions with both traditional, kinematic smoothing constraints on slip and a simple physical condition of uniform stress
Parameter and Structure Inference for Nonlinear Dynamical Systems
Morris, Robin D.; Smelyanskiy, Vadim N.; Millonas, Mark
2006-01-01
A great many systems can be modeled in the non-linear dynamical systems framework, as x = f(x) + xi(t), where f() is the potential function for the system, and xi is the excitation noise. Modeling the potential using a set of basis functions, we derive the posterior for the basis coefficients. A more challenging problem is to determine the set of basis functions that are required to model a particular system. We show that using the Bayesian Information Criteria (BIC) to rank models, and the beam search technique, that we can accurately determine the structure of simple non-linear dynamical system models, and the structure of the coupling between non-linear dynamical systems where the individual systems are known. This last case has important ecological applications.
Nonlinear wave propagation studies, dispersion modeling, and signal parameters correction
Czech Academy of Sciences Publication Activity Database
Převorovský, Zdeněk
..: ..., 2004, 00. [European Workshop on FP6-AERONEWS /1./. Naples (IT), 13.09.2004-16.09.2004] EU Projects: European Commission(XE) 502927 - AERO-NEWS Institutional research plan: CEZ:AV0Z2076919 Keywords : nodestructive testing * nonlinear elastic wave spectroscopy Subject RIV: BI - Acoustics
Parameter spaces for linear and nonlinear whistler-mode waves
International Nuclear Information System (INIS)
Summers, Danny; Tang, Rongxin; Omura, Yoshiharu; Lee, Dong-Hun
2013-01-01
We examine the growth of magnetospheric whistler-mode waves which comprises a linear growth phase followed by a nonlinear growth phase. We construct time-profiles for the wave amplitude that smoothly match at the transition between linear and nonlinear wave growth. This matching procedure can only take place over a limited “matching region” in (N h /N 0 ,A T )-space, where A T is the electron thermal anisotropy, N h is the hot (energetic) electron number density, and N 0 is the cold (background) electron number density. We construct this matching region and determine how the matching wave amplitude varies throughout the region. Further, we specify a boundary in (N h /N 0 ,A T )-space that separates a region where only linear chorus wave growth can occur from the region in which fully nonlinear chorus growth is possible. We expect that this boundary should prove of practical use in performing computationally expensive full-scale particle simulations, and in interpreting experimental wave data
International Nuclear Information System (INIS)
Sarrach, D.; Strohner, P.
1986-01-01
The Gauss-Newton algorithm has been used to evaluate tracer binding parameters of RIA by nonlinear regression analysis. The calculations were carried out on the K1003 desk computer. Equations for simple binding models and its derivatives are presented. The advantages of nonlinear regression analysis over linear regression are demonstrated
Performance emulation and parameter estimation for nonlinear fibre-optic links
DEFF Research Database (Denmark)
Piels, Molly; Porto da Silva, Edson; Zibar, Darko
2016-01-01
Fibre-optic communication systems, especially when operating in the nonlinear regime, generally do not perform exactly as theory would predict. A number of methods for data-based evaluation of nonlinear fibre-optic link parameters, both for accurate performance emulation and optimization...
Non-linearity parameter of binary liquid mixtures at elevated pressures
Indian Academy of Sciences (India)
. Ultrasonic studies in liquid mixtures provide valuable information about structure and interaction in such systems. The present investigation comprises of theoretical evaluation of the acoustic non-linearity parameter / of four binary liquid ...
Wu, Hui; Hu, Liming; Wen, Qingbo
2017-06-01
Electro-osmotic consolidation is an effective method for soft ground improvement. A main limitation of previous numerical models on this technique is the ignorance of the non-linear variation of soil parameters. In the present study, a multi-field numerical model is developed with the consideration of the non-linear variation of soil parameters during electro-osmotic consolidation process. The numerical simulations on an axisymmetric model indicated that the non-linear variation of soil parameters showed remarkable impact on the development of the excess pore water pressure and degree of consolidation. A field experiment with complex geometry, boundary conditions, electrode configuration and voltage application was further simulated with the developed numerical model. The comparison between field and numerical data indicated that the numerical model coupling of the non-linear variation of soil parameters gave more reasonable results. The developed numerical model is capable to analyze engineering cases with complex operating conditions.
Energy Technology Data Exchange (ETDEWEB)
Jeong, Hyun Jo; Cho, Sung Jong; Nam, Ki Woong; Lee, Jang Hyun [Division of Mechanical and Automotive Engineering, Wonkwang University, Iksan (Korea, Republic of)
2016-04-15
The nonlinearity parameter is frequently measured as a sensitive indicator in damaged material characterization or tissue harmonic imaging. Several previous studies have employed the plane wave solution, and ignored the effects of beam diffraction when measuring the non-linearity parameter β. This paper presents a multi-Gaussian beam approach to explicitly derive diffraction corrections for fundamental and second harmonics under quasilinear and paraxial approximation. Their effects on the nonlinearity parameter estimation demonstrate complicated dependence of β on the transmitter-receiver geometries, frequency, and propagation distance. The diffraction effects on the non-linearity parameter estimation are important even in the nearfield region. Experiments are performed to show that improved β values can be obtained by considering the diffraction effects.
Estimation of delays and other parameters in nonlinear functional differential equations
Banks, H. T.; Lamm, P. K. D.
1983-01-01
A spline-based approximation scheme for nonlinear nonautonomous delay differential equations is discussed. Convergence results (using dissipative type estimates on the underlying nonlinear operators) are given in the context of parameter estimation problems which include estimation of multiple delays and initial data as well as the usual coefficient-type parameters. A brief summary of some of the related numerical findings is also given.
Evaluation of third order nonlinear optical parameters of CdS/PVA nanocomposite
Energy Technology Data Exchange (ETDEWEB)
Sharma, Mamta [Department of Physics, Center of Advanced Study in Physics, Panjab University, Chandigarh-160014 (India); Department of Applied Sciences (Physics), UIET, Panjab University, Chandigarh-160014 (India); Tripathi, S. K., E-mail: surya@pu.ac.in, E-mail: surya-tr@yahoo.com [Department of Physics, Center of Advanced Study in Physics, Panjab University, Chandigarh-160014 (India)
2015-06-24
CdS nanoparticles dispersed in PVA are prepared by Chemical method at room temperature. The nonlinear optical parameters such as nonlinear absorption (β), nonlinear refractive index (n{sub 2}) and nonlinear susceptibility (χ{sup 3}) are calculated for this sample by using Z-scan technique. CdS/PVA samples show the two photon absorption mechanism. The third order nonlinear susceptibility is calculated from n{sub 2} and β and is found to be of the order of 10{sup −7} – 10{sup −8} m{sup 2}/V{sup 2}. The larger value of third order nonlinear susceptibility is due to dielectric and quantum confinement effect.
Control and Estimation of Distributed Parameter Systems
Kappel, F; Kunisch, K
1998-01-01
Consisting of 23 refereed contributions, this volume offers a broad and diverse view of current research in control and estimation of partial differential equations. Topics addressed include, but are not limited to - control and stability of hyperbolic systems related to elasticity, linear and nonlinear; - control and identification of nonlinear parabolic systems; - exact and approximate controllability, and observability; - Pontryagin's maximum principle and dynamic programming in PDE; and - numerics pertinent to optimal and suboptimal control problems. This volume is primarily geared toward control theorists seeking information on the latest developments in their area of expertise. It may also serve as a stimulating reader to any researcher who wants to gain an impression of activities at the forefront of a vigorously expanding area in applied mathematics.
HIROSE,Hideo
1998-01-01
TYPES OF THE DISTRIBUTION:13;Normal distribution (2-parameter)13;Uniform distribution (2-parameter)13;Exponential distribution ( 2-parameter)13;Weibull distribution (2-parameter)13;Gumbel Distribution (2-parameter)13;Weibull/Frechet Distribution (3-parameter)13;Generalized extreme-value distribution (3-parameter)13;Gamma distribution (3-parameter)13;Extended Gamma distribution (3-parameter)13;Log-normal distribution (3-parameter)13;Extended Log-normal distribution (3-parameter)13;Generalized ...
Nonlinear adaptive control system design with asymptotically stable parameter estimation error
Mishkov, Rumen; Darmonski, Stanislav
2018-01-01
The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.
Directory of Open Access Journals (Sweden)
Shaolong Chen
2016-01-01
Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.
Likelihood Inference of Nonlinear Models Based on a Class of Flexible Skewed Distributions
Directory of Open Access Journals (Sweden)
Xuedong Chen
2014-01-01
Full Text Available This paper deals with the issue of the likelihood inference for nonlinear models with a flexible skew-t-normal (FSTN distribution, which is proposed within a general framework of flexible skew-symmetric (FSS distributions by combining with skew-t-normal (STN distribution. In comparison with the common skewed distributions such as skew normal (SN, and skew-t (ST as well as scale mixtures of skew normal (SMSN, the FSTN distribution can accommodate more flexibility and robustness in the presence of skewed, heavy-tailed, especially multimodal outcomes. However, for this distribution, a usual approach of maximum likelihood estimates based on EM algorithm becomes unavailable and an alternative way is to return to the original Newton-Raphson type method. In order to improve the estimation as well as the way for confidence estimation and hypothesis test for the parameters of interest, a modified Newton-Raphson iterative algorithm is presented in this paper, based on profile likelihood for nonlinear regression models with FSTN distribution, and, then, the confidence interval and hypothesis test are also developed. Furthermore, a real example and simulation are conducted to demonstrate the usefulness and the superiority of our approach.
Energy Technology Data Exchange (ETDEWEB)
McCarty, Rachael; Nima Mahmoodi, S., E-mail: nmahmoodi@eng.ua.edu [Department of Mechanical Engineering, The University of Alabama, Box 870276, Tuscaloosa, Alabama 35487 (United States)
2014-02-21
The equations of motion for a piezoelectric microcantilever are derived for a nonlinear contact force. The analytical expressions for natural frequencies and mode shapes are obtained. Then, the method of multiple scales is used to analyze the analytical frequency response of the piezoelectric probe. The effects of nonlinear excitation force on the microcantilever beam's frequency and amplitude are analytically studied. The results show a frequency shift in the response resulting from the force nonlinearities. This frequency shift during contact mode is an important consideration in the modeling of AFM mechanics for generation of more accurate imaging. Also, a sensitivity analysis of the system parameters on the nonlinearity effect is performed. The results of a sensitivity analysis show that it is possible to choose parameters such that the frequency shift minimizes. Certain parameters such as tip radius, microcantilever beam dimensions, and modulus of elasticity have more influence on the nonlinearity of the system than other parameters. By changing only three parameters—tip radius, thickness, and modulus of elasticity of the microbeam—a more than 70% reduction in nonlinearity effect was achieved.
Multiplicity distributions in impact parameter space
International Nuclear Information System (INIS)
Wakano, Masami
1976-01-01
A definition for the average multiplicity of pions as a function of momentum transfer and total energy in the high energy proton-proton collisions is proposed by using the n-pion production differential cross section with the given momentum transfer from a proton to other final products and the given energy of the latter. Contributions from nondiffractive and diffractive processes are formulated in a multi-Regge model. We define a relationship between impact parameter and momentum transfer in the sense of classical theory for inelastic processes and we obtain the average multiplicity of pions as a function of impact parameter and total energy from the corresponding quantity afore-mentioned. By comparing this quantity with the square root of the opaqueness at given impact parameter, we conclude that the overlap of localized constituents is important in determining the opaqueness at given impact parameter in a collision of two hadrons. (auth.)
PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.
Xia, Jing; Wang, Michelle Yongmei
Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.
Adaptive control of nonlinear in parameters chaotic system via Lyapunov exponents placement
Energy Technology Data Exchange (ETDEWEB)
Ayati, Moosa [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran (Iran, Islamic Republic of)], E-mail: Ayati@dena.kntu.ac.ir; Khaki-Sedigh, Ali [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran (Iran, Islamic Republic of)], E-mail: sedigh@kntu.ac.ir
2009-08-30
This paper proposes a new method for the adaptive control of nonlinear in parameters (NLP) chaotic systems. A method based on Lagrangian of a cost function is used to identify the parameters of the system. Estimation results are used to calculate the Lyapunov exponents adaptively. Finally, the Lyapunov exponents placement method is used to assign the desired Lyapunov exponents of the closed loop system.
Adaptive control of nonlinear in parameters chaotic system via Lyapunov exponents placement
International Nuclear Information System (INIS)
Ayati, Moosa; Khaki-Sedigh, Ali
2009-01-01
This paper proposes a new method for the adaptive control of nonlinear in parameters (NLP) chaotic systems. A method based on Lagrangian of a cost function is used to identify the parameters of the system. Estimation results are used to calculate the Lyapunov exponents adaptively. Finally, the Lyapunov exponents placement method is used to assign the desired Lyapunov exponents of the closed loop system.
Distributed robust adaptive control of high order nonlinear multi agent systems.
Hashemi, Mahnaz; Shahgholian, Ghazanfar
2018-03-01
In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
A penalized framework for distributed lag non-linear models.
Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G
2017-09-01
Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
Nonlinear Parameter Identification of a Resonant Electrostatic MEMS Actuator
Al-Ghamdi, Majed S.; Alneamy, Ayman M.; Park, Sangtak; Li, Beichen; Khater, Mahmoud E.; Abdel-Rahman, Eihab M.; Heppler, Glenn R.; Yavuz, Mustafa
2017-01-01
We experimentally investigate the primary superharmonic of order two and subharmonic of order one-half resonances of an electrostatic MEMS actuator under direct excitation. We identify the parameters of a one degree of freedom (1-DOF) generalized Duffing oscillator model representing it. The experiments were conducted in soft vacuum to reduce squeeze-film damping, and the actuator response was measured optically using a laser vibrometer. The predictions of the identified model were found to be in close agreement with the experimental results. We also identified the noise spectral density of process (actuation voltage) and measurement noise. PMID:28505097
Wang, Chenliang; Wen, Changyun; Hu, Qinglei; Wang, Wei; Zhang, Xiuyu
2018-06-01
This paper is devoted to distributed adaptive containment control for a class of nonlinear multiagent systems with input quantization. By employing a matrix factorization and a novel matrix normalization technique, some assumptions involving control gain matrices in existing results are relaxed. By fusing the techniques of sliding mode control and backstepping control, a two-step design method is proposed to construct controllers and, with the aid of neural networks, all system nonlinearities are allowed to be unknown. Moreover, a linear time-varying model and a similarity transformation are introduced to circumvent the obstacle brought by quantization, and the controllers need no information about the quantizer parameters. The proposed scheme is able to ensure the boundedness of all closed-loop signals and steer the containment errors into an arbitrarily small residual set. The simulation results illustrate the effectiveness of the scheme.
Estimation of Aircraft Nonlinear Unsteady Parameters From Wind Tunnel Data
Klein, Vladislav; Murphy, Patrick C.
1998-01-01
Aerodynamic equations were formulated for an aircraft in one-degree-of-freedom large amplitude motion about each of its body axes. The model formulation based on indicial functions separated the resulting aerodynamic forces and moments into static terms, purely rotary terms and unsteady terms. Model identification from experimental data combined stepwise regression and maximum likelihood estimation in a two-stage optimization algorithm that can identify the unsteady term and rotary term if necessary. The identification scheme was applied to oscillatory data in two examples. The model identified from experimental data fit the data well, however, some parameters were estimated with limited accuracy. The resulting model was a good predictor for oscillatory and ramp input data.
Binomial distribution for the charge asymmetry parameter
International Nuclear Information System (INIS)
Chou, T.T.; Yang, C.N.
1984-01-01
It is suggested that for high energy collisions the distribution with respect to the charge asymmetry z = nsub(F) - nsub(B) is binomial, where nsub(F) and nsub(B) are the forward and backward charge multiplicities. (orig.)
Performance parameters of electric power distribution
International Nuclear Information System (INIS)
Schilling, M.Th.; Lima, J.W.M.
1992-01-01
The aspects referring to the evaluation of distribution system reliability are presented: consumers, companies and regulator institutes. The different strategies for fixing of probabilistic criterions of performance are mentioned, including the economic valorization of continuity restriction of electric supply. (C.G.C.)
International Nuclear Information System (INIS)
Xu Ruirui; Chen Tianlun; Gao Chengfeng
2006-01-01
Nonlinear time series prediction is studied by using an improved least squares support vector machine (LS-SVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization. We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.
State and parameter estimation in nonlinear systems as an optimal tracking problem
International Nuclear Information System (INIS)
Creveling, Daniel R.; Gill, Philip E.; Abarbanel, Henry D.I.
2008-01-01
In verifying and validating models of nonlinear processes it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, we present a framework for connecting a data signal with a model in a way that minimizes the required coupling yet allows the estimation of unknown parameters in the model. The need to evaluate unknown parameters in models of nonlinear physical, biophysical, and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. Our approach builds on existing work that uses synchronization as a tool for parameter estimation. We address some of the critical issues in that work and provide a practical framework for finding an accurate solution. In particular, we show the equivalence of this problem to that of tracking within an optimal control framework. This equivalence allows the application of powerful numerical methods that provide robust practical tools for model development and validation
A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems
Liu, Zuolin; Xu, Jian
2018-04-01
In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.
Nonlinear System Identification Using Quasi-ARX RBFN Models with a Parameter-Classified Scheme
Directory of Open Access Journals (Sweden)
Lan Wang
2017-01-01
Full Text Available Quasi-linear autoregressive with exogenous inputs (Quasi-ARX models have received considerable attention for their usefulness in nonlinear system identification and control. In this paper, identification methods of quasi-ARX type models are reviewed and categorized in three main groups, and a two-step learning approach is proposed as an extension of the parameter-classified methods to identify the quasi-ARX radial basis function network (RBFN model. Firstly, a clustering method is utilized to provide statistical properties of the dataset for determining the parameters nonlinear to the model, which are interpreted meaningfully in the sense of interpolation parameters of a local linear model. Secondly, support vector regression is used to estimate the parameters linear to the model; meanwhile, an explicit kernel mapping is given in terms of the nonlinear parameter identification procedure, in which the model is transformed from the nonlinear-in-nature to the linear-in-parameter. Numerical and real cases are carried out finally to demonstrate the effectiveness and generalization ability of the proposed method.
Fast non-linear extraction of plasma equilibrium parameters using a neural network mapping
International Nuclear Information System (INIS)
Lister, J.B.; Schnurrenberger, H.
1990-07-01
The shaping of non-circular plasmas requires a non-linear mapping between the measured diagnostic signals and selected equilibrium parameters. The particular configuration of Neural Network known as the multi-layer perceptron provides a powerful and general technique for formulating an arbitrary continuous non-linear multi-dimensional mapping. This technique has been successfully applied to the extraction of equilibrium parameters from measurements of single-null diverted plasmas in the DIII-D tokamak; the results are compared with a purely linear mapping. The method is promising, and hardware implementation is straightforward. (author) 15 refs., 7 figs
International Nuclear Information System (INIS)
Frolov, A.M.
1986-01-01
The problem of exact variational calculations of few-particle systems in the exponential basis of the relative coordinates using nonlinear parameters is studied. The techniques of stepwise optimization and global chaos of nonlinear parameters are used to calculate the S and P states of homonuclear muonic molecules with an error of no more than +0.001 eV. The global-chaos technique also has proved to be successful in the case of the nuclear systems 3 H and 3 He
Fast non-linear extraction of plasma equilibrium parameters using a neural network mapping
International Nuclear Information System (INIS)
Lister, J.B.; Schnurrenberger, H.
1991-01-01
The shaping of non-circular plasmas requires a non-linear mapping between the measured diagnostic signals and selected equilibrium parameters. The particular configuration of neural network known as the multilayer perceptron provides a powerful and general technique for formulating an arbitrary continuous non-linear multi-dimensional mapping. This technique has been successfully applied to the extraction of equilibrium parameters from measurements of single-null diverted plasmas in the DIII-D tokamak; the results are compared with a purely linear mapping. The method is promising, and hardware implementation is straightforward. (author). 17 refs, 8 figs, 2 tab
International Nuclear Information System (INIS)
Zhao, Chao; Vu, Quoc Dong; Li, Pu
2013-01-01
A three-stage computation framework for solving parameter estimation problems for dynamic systems with multiple data profiles is developed. The dynamic parameter estimation problem is transformed into a nonlinear programming (NLP) problem by using collocation on finite elements. The model parameters to be estimated are treated in the upper stage by solving an NLP problem. The middle stage consists of multiple NLP problems nested in the upper stage, representing the data reconciliation step for each data profile. We use the quasi-sequential dynamic optimization approach to solve these problems. In the lower stage, the state variables and their gradients are evaluated through ntegrating the model equations. Since the second-order derivatives are not required in the computation framework this proposed method will be efficient for solving nonlinear dynamic parameter estimation problems. The computational results obtained on a parameter estimation problem for two CSTR models demonstrate the effectiveness of the proposed approach
Energy Technology Data Exchange (ETDEWEB)
Zhao, Chao [FuZhou University, FuZhou (China); Vu, Quoc Dong; Li, Pu [Ilmenau University of Technology, Ilmenau (Germany)
2013-02-15
A three-stage computation framework for solving parameter estimation problems for dynamic systems with multiple data profiles is developed. The dynamic parameter estimation problem is transformed into a nonlinear programming (NLP) problem by using collocation on finite elements. The model parameters to be estimated are treated in the upper stage by solving an NLP problem. The middle stage consists of multiple NLP problems nested in the upper stage, representing the data reconciliation step for each data profile. We use the quasi-sequential dynamic optimization approach to solve these problems. In the lower stage, the state variables and their gradients are evaluated through ntegrating the model equations. Since the second-order derivatives are not required in the computation framework this proposed method will be efficient for solving nonlinear dynamic parameter estimation problems. The computational results obtained on a parameter estimation problem for two CSTR models demonstrate the effectiveness of the proposed approach.
Study on Nonlinear Vibration Analysis of Gear System with Random Parameters
Tong, Cao; Liu, Xiaoyuan; Fan, Li
2018-03-01
In order to study the dynamic characteristics of gear nonlinear vibration system and the influence of random parameters, firstly, a nonlinear stochastic vibration analysis model of gear 3-DOF is established based on Newton’s Law. And the random response of gear vibration is simulated by stepwise integration method. Secondly, the influence of stochastic parameters such as meshing damping, tooth side gap and excitation frequency on the dynamic response of gear nonlinear system is analyzed by using the stability analysis method such as bifurcation diagram and Lyapunov exponent method. The analysis shows that the stochastic process can not be neglected, which can cause the random bifurcation and chaos of the system response. This study will provide important reference value for vibration engineering designers.
A Comparative Study of Distribution System Parameter Estimation Methods
Energy Technology Data Exchange (ETDEWEB)
Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup
2016-07-17
In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of both methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.
Nonlinear soil parameter effects on dynamic embedment of offshore pipeline on soft clay
Directory of Open Access Journals (Sweden)
Su Young Yu
2015-03-01
Full Text Available In this paper, the effects of nonlinear soft clay on dynamic embedment of offshore pipeline were investigated. Seabed embedment by pipe-soil interactions has impacts on the structural boundary conditions for various subsea structures such as pipeline, riser, pile, and many other systems. A number of studies have been performed to estimate real soil behavior, but their estimation of seabed embedment has not been fully identified and there are still many uncertainties. In this regards, comparison of embedment between field survey and existing empirical models has been performed to identify uncertainties and investigate the effect of nonlinear soil parameter on dynamic embedment. From the comparison, it is found that the dynamic embedment with installation effects based on nonlinear soil model have an influence on seabed embedment. Therefore, the pipe embedment under dynamic condition by nonlinear para- meters of soil models was investigated by Dynamic Embedment Factor (DEF concept, which is defined as the ratio of the dynamic and static embedment of pipeline, in order to overcome the gap between field embedment and currently used empirical and numerical formula. Although DEF through various researches is suggested, its range is too wide and it does not consider dynamic laying effect. It is difficult to find critical parameters that are affecting to the embedment result. Therefore, the study on dynamic embedment factor by soft clay parameters of nonlinear soil model was conducted and the sensitivity analyses about parameters of nonlinear soil model were performed as well. The tendency on dynamic embedment factor was found by conducting numerical analyses using OrcaFlex software. It is found that DEF was influenced by shear strength gradient than other factors. The obtained results will be useful to understand the pipe embedment on soft clay seabed for applying offshore pipeline designs such as on-bottom stability and free span analyses.
National Aeronautics and Space Administration — The overall goal of the project is to develop reliable reduced order modeling technologies to automatically generate nonlinear, parameter-varying (PV),...
Solliton-like order parameter distributions in the critical region
Directory of Open Access Journals (Sweden)
A.V.Babich
2006-01-01
Full Text Available Some exact one-component order parameter distributions for the Michelson thermodynamic potential are obtained. The phase transition of second kind in Ginzburg-Landau type model is investigated. The exact partial distribution of the order parameter in the form of Jakobi elliptic function is obtained. The energy of this distribution is lower at some temperature interval than for the best known models.
Directory of Open Access Journals (Sweden)
Milovanović Branislav
2007-01-01
Full Text Available Introduction: There are different proofs about association of autonomic nervous system dysfunction, especially nonlinear parameters, with higher mortality after myocardial infarction. Objective The objective of the study was to determine predictive value of Poincare plot as nonlinear parameter and other significant standard risk predictors: ejection fraction of the left ventricle, late potentials, ventricular arrhythmias, and QT interval. Method The study included 1081 patients with mean follow up of 28 months (ranging fom 0-80 months. End-point of the study was cardiovascular mortality. The following diagnostic methods were used during the second week: ECG with commercial software Schiller AT-10: short time spectral analysis of RR variability with analysis of Poincare plot as nonlinear parameter and late potentials; 24-hour ambulatory ECG monitoring: QT interval, RR interval, QT/RR slope, ventricular arrhythmias (Lown >II; echocardiography examinations: systolic disorder (defined as EF<40 %. Results There were 103 (9.52% cardiovascular deaths during the follow-up. In univariate analysis, the following parameters were significantly correlated with mortality: mean RR interval < 800 ms, QT and RR interval space relationship as mean RR interval < 800 ms and QT interval > 350 ms, positive late potentials, systolic dysfunction, Poincare plot as a point, ventricular arrhythmias (Lown > II. In multivariate analysis, the significant risk predictors were: Poincare plot as a point and mean RR interval lower than 800 ms. Conclusion Mean RR interval lower than 800 ms and nonlinear and space presentation of RR interval as a point Poincare plot were multivariate risk predictors.
Directory of Open Access Journals (Sweden)
Hailong Zhu
2012-01-01
Full Text Available The existence and multiplicity of solutions for second-order differential equations with a parameter are discussed in this paper. We are mainly concerned with the semipositone case. The analysis relies on the nonlinear alternative principle of Leray-Schauder and Krasnosel'skii's fixed point theorem in cones.
Iterative method of the parameter variation for solution of nonlinear functional equations
International Nuclear Information System (INIS)
Davidenko, D.F.
1975-01-01
The iteration method of parameter variation is used for solving nonlinear functional equations in Banach spaces. The authors consider some methods for numerical integration of ordinary first-order differential equations and construct the relevant iteration methods of parameter variation, both one- and multifactor. They also discuss problems of mathematical substantiation of the method, study the conditions and rate of convergence, estimate the error. The paper considers the application of the method to specific functional equations
Kim, Gun; Kim, Jin-Yeon; Kurtis, Kimberly E.; Jacobs, Laurence J.
2015-03-01
This research experimentally investigates the sensitivity of the acoustic nonlinearity parameter to microcracks in cement-based materials. Based on the second harmonic generation (SHG) technique, an experimental setup using non-contact, air-coupled detection is used to receive the consistent Rayleigh surface waves. To induce variations in the extent of microscale cracking in two types of specimens (concrete and mortar), shrinkage reducing admixture (SRA), is used in one set, while a companion specimen is prepared without SRA. A 50 kHz wedge transducer and a 100 kHz air-coupled transducer are implemented for the generation and detection of nonlinear Rayleigh waves. It is shown that the air-coupled detection method provides more repeatable fundamental and second harmonic amplitudes of the propagating Rayleigh waves. The obtained amplitudes are then used to calculate the relative nonlinearity parameter βre, the ratio of the second harmonic amplitude to the square of the fundamental amplitude. The experimental results clearly demonstrate that the nonlinearity parameter (βre) is highly sensitive to the microstructural changes in cement-based materials than the Rayleigh phase velocity and attenuation and that SRA has great potential to avoid shrinkage cracking in cement-based materials.
Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models
Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.
2011-01-01
We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.
Sun, C. T.; Yoon, K. J.
1990-01-01
A one-parameter plasticity model was shown to adequately describe the orthotropic plastic deformation of AS4/PEEK (APC-2) unidirectional thermoplastic composite. This model was verified further for unidirectional and laminated composite panels with and without a hole. The nonlinear stress-strain relations were measured and compared with those predicted by the finite element analysis using the one-parameter elastic-plastic constitutive model. The results show that the one-parameter orthotropic plasticity model is suitable for the analysis of elastic-plastic deformation of AS4/PEEK composite laminates.
Árnadóttir, Í.; Gíslason, M. K.; Carraro, U.
2016-01-01
Muscle degeneration has been consistently identified as an independent risk factor for high mortality in both aging populations and individuals suffering from neuromuscular pathology or injury. While there is much extant literature on its quantification and correlation to comorbidities, a quantitative gold standard for analyses in this regard remains undefined. Herein, we hypothesize that rigorously quantifying entire radiodensitometric distributions elicits more muscle quality information than average values reported in extant methods. This study reports the development and utility of a nonlinear trimodal regression analysis method utilized on radiodensitometric distributions of upper leg muscles from CT scans of a healthy young adult, a healthy elderly subject, and a spinal cord injury patient. The method was then employed with a THA cohort to assess pre- and postsurgical differences in their healthy and operative legs. Results from the initial representative models elicited high degrees of correlation to HU distributions, and regression parameters highlighted physiologically evident differences between subjects. Furthermore, results from the THA cohort echoed physiological justification and indicated significant improvements in muscle quality in both legs following surgery. Altogether, these results highlight the utility of novel parameters from entire HU distributions that could provide insight into the optimal quantification of muscle degeneration. PMID:28115982
Directory of Open Access Journals (Sweden)
K. J. Edmunds
2016-01-01
Full Text Available Muscle degeneration has been consistently identified as an independent risk factor for high mortality in both aging populations and individuals suffering from neuromuscular pathology or injury. While there is much extant literature on its quantification and correlation to comorbidities, a quantitative gold standard for analyses in this regard remains undefined. Herein, we hypothesize that rigorously quantifying entire radiodensitometric distributions elicits more muscle quality information than average values reported in extant methods. This study reports the development and utility of a nonlinear trimodal regression analysis method utilized on radiodensitometric distributions of upper leg muscles from CT scans of a healthy young adult, a healthy elderly subject, and a spinal cord injury patient. The method was then employed with a THA cohort to assess pre- and postsurgical differences in their healthy and operative legs. Results from the initial representative models elicited high degrees of correlation to HU distributions, and regression parameters highlighted physiologically evident differences between subjects. Furthermore, results from the THA cohort echoed physiological justification and indicated significant improvements in muscle quality in both legs following surgery. Altogether, these results highlight the utility of novel parameters from entire HU distributions that could provide insight into the optimal quantification of muscle degeneration.
International Nuclear Information System (INIS)
Masalov, Anatolii V; Chudnovsky, Aleksandr V
2004-01-01
It is shown that the finite thickness of the second-harmonic crystal distorts the results of measurements in nonlinear autocorrelators intended for measuring the durations and fields of femtosecond light pulses mainly due to dispersive broadening (or compression) of the pulses being measured, as well as due to the group velocity mismatch between the fundamental and sum-frequency pulses. The refractive index dispersion of the crystal, scaled by half its thickness, distorts the pulse duration to a certain extent depending on its initial chirp and thus determines the width of the energy distribution recorded in the autocorrelator. As the crystal thickness increases, the group velocity mismatch leads to a transformation of the recorded distribution from the correlation function of intensity to the squared modulus of the field correlation function. In the case of Gaussian pulses, such a transformation does not affect significantly the recorded distribution. Errors of pulse duration measurements are estimated. (nonlinear optical phenomena)
On the distribution of plasma parameters in RF glow discharge
International Nuclear Information System (INIS)
Ning Cheng; Liu Zuli; Liu Donghui; Han Caiyuan.
1993-01-01
A self-consistent numerical model based on the two-fluid equations for describing the transport of charged particles in the RF glow discharge is presented. For a plasma generator filled with low-pressure air and parallel-plate electrodes, the model is numerical solved. The space-time distribution of parameters and the spatial distribution of some time-averaged parameters in plasma, which show the physical picture of the RF glow discharge, are obtained
Directory of Open Access Journals (Sweden)
U. Filobello-Nino
2015-01-01
Full Text Available We propose an approximate solution of T-F equation, obtained by using the nonlinearities distribution homotopy perturbation method (NDHPM. Besides, we show a table of comparison, between this proposed approximate solution and a numerical of T-F, by establishing the accuracy of the results.
Energy Technology Data Exchange (ETDEWEB)
Smith, Scott A [Univ. of Maryland Baltimore County (UMBC), Baltimore, MD (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Catalfamo, Simone [Univ. of Stuttgart (Germany); Brake, Matthew R. W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rice Univ., Houston, TX (United States); Schwingshackl, Christoph W. [Imperial College, London (United Kingdom); Reusb, Pascal [Daimler AG, Stuttgart (Germany)
2017-01-01
In the study of the dynamics of nonlinear systems, experimental measurements often convolute the response of the nonlinearity of interest and the effects of the experimental setup. To reduce the influence of the experimental setup on the deduction of the parameters of the nonlinearity, the response of a mechanical joint is investigated under various experimental setups. These experiments first focus on quantifying how support structures and measurement techniques affect the natural frequency and damping of a linear system. The results indicate that support structures created from bungees have negligible influence on the system in terms of frequency and damping ratio variations. The study then focuses on the effects of the excitation technique on the response for a linear system. The findings suggest that thinner stingers should not be used, because under the high force requirements the stinger bending modes are excited adding unwanted torsional coupling. The optimal configuration for testing the linear system is then applied to a nonlinear system in order to assess the robustness of the test configuration. Finally, recommendations are made for conducting experiments on nonlinear systems using conventional/linear testing techniques.
DEFF Research Database (Denmark)
Sommer, Helle Mølgaard; Holst, Helle; Spliid, Henrik
1995-01-01
Three identical microbiological experiments were carried out and analysed in order to examine the variability of the parameter estimates. The microbiological system consisted of a substrate (toluene) and a biomass (pure culture) mixed together in an aquifer medium. The degradation of the substrate...... and the growth of the biomass are described by the Monod model consisting of two nonlinear coupled first-order differential equations. The objective of this study was to estimate the kinetic parameters in the Monod model and to test whether the parameters from the three identical experiments have the same values....... Estimation of the parameters was obtained using an iterative maximum likelihood method and the test used was an approximative likelihood ratio test. The test showed that the three sets of parameters were identical only on a 4% alpha level....
International Nuclear Information System (INIS)
Ma Huanfei; Lin Wei
2009-01-01
The existing adaptive synchronization technique based on the stability theory and invariance principle of dynamical systems, though theoretically proved to be valid for parameters identification in specific models, is always showing slow convergence rate and even failed in practice when the number of parameters becomes large. Here, for parameters update, a novel nonlinear adaptive rule is proposed to accelerate the rate. Its feasibility is validated by analytical arguments as well as by specific parameters identification in the Lotka-Volterra model with multiple species. Two adjustable factors in this rule influence the identification accuracy, which means that a proper choice of these factors leads to an optimal performance of this rule. In addition, a feasible method for avoiding the occurrence of the approximate linear dependence among terms with parameters on the synchronized manifold is also proposed.
Heidari, M.; Ranjithan, S.R.
1998-01-01
In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is
Non-Linear Metamodeling Extensions to the Robust Parameter Design of Computer Simulations
2016-09-15
The combined-array RSM approach has been applied to a piston simulation [11] and an economic order quantity inventory model [12, 13]. A textbook ...are limited when applied to simulations. In the former case, the mean and variance models can be inadequate due to a high level of non-linearity...highly non-linear nature of typical simulations. In the multi-response RPD problem, the objective is to find the optimal control parameter levels
Positive solutions for a nonlinear periodic boundary-value problem with a parameter
Directory of Open Access Journals (Sweden)
Jingliang Qiu
2012-08-01
Full Text Available Using topological degree theory with a partially ordered structure of space, sufficient conditions for the existence and multiplicity of positive solutions for a second-order nonlinear periodic boundary-value problem are established. Inspired by ideas in Guo and Lakshmikantham [6], we study the dependence of positive periodic solutions as a parameter approaches infinity, $$ lim_{lambdao +infty}|x_{lambda}|=+infty,quadhbox{or}quad lim_{lambdao+infty}|x_{lambda}|=0. $$
Improved Accuracy of Nonlinear Parameter Estimation with LAV and Interval Arithmetic Methods
Directory of Open Access Journals (Sweden)
Humberto Muñoz
2009-06-01
Full Text Available The reliable solution of nonlinear parameter es- timation problems is an important computational problem in many areas of science and engineering, including such applications as real time optimization. Its goal is to estimate accurate model parameters that provide the best ﬁt to measured data, despite small- scale noise in the data or occasional large-scale mea- surement errors (outliers. In general, the estimation techniques are based on some kind of least squares or maximum likelihood criterion, and these require the solution of a nonlinear and non-convex optimiza- tion problem. Classical solution methods for these problems are local methods, and may not be reliable for ﬁnding the global optimum, with no guarantee the best model parameters have been found. Interval arithmetic can be used to compute completely and reliably the global optimum for the nonlinear para- meter estimation problem. Finally, experimental re- sults will compare the least squares, l2, and the least absolute value, l1, estimates using interval arithmetic in a chemical engineering application.
Cao, Jiguo; Huang, Jianhua Z.; Wu, Hulin
2012-01-01
Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online.
Distributed Cooperative Control of Nonlinear and Non-identical Multi-agent Systems
DEFF Research Database (Denmark)
Bidram, Ali; Lewis, Frank; Davoudi, Ali
2013-01-01
This paper exploits input-output feedback linearization technique to implement distributed cooperative control of multi-agent systems with nonlinear and non-identical dynamics. Feedback linearization transforms the synchronization problem for a nonlinear and heterogeneous multi-agent system...... for electric power microgrids. The effectiveness of the proposed control is verified by simulating a microgrid test system....
International Nuclear Information System (INIS)
Kaltenbacher, Barbara; Kirchner, Alana; Vexler, Boris
2011-01-01
Parameter identification problems for partial differential equations usually lead to nonlinear inverse problems. A typical property of such problems is their instability, which requires regularization techniques, like, e.g., Tikhonov regularization. The main focus of this paper will be on efficient methods for determining a suitable regularization parameter by using adaptive finite element discretizations based on goal-oriented error estimators. A well-established method for the determination of a regularization parameter is the discrepancy principle where the residual norm, considered as a function i of the regularization parameter, should equal an appropriate multiple of the noise level. We suggest to solve the resulting scalar nonlinear equation by an inexact Newton method, where in each iteration step, a regularized problem is solved at a different discretization level. The proposed algorithm is an extension of the method suggested in Griesbaum A et al (2008 Inverse Problems 24 025025) for linear inverse problems, where goal-oriented error estimators for i and its derivative are used for adaptive refinement strategies in order to keep the discretization level as coarse as possible to save computational effort but fine enough to guarantee global convergence of the inexact Newton method. This concept leads to a highly efficient method for determining the Tikhonov regularization parameter for nonlinear ill-posed problems. Moreover, we prove that with the so-obtained regularization parameter and an also adaptively discretized Tikhonov minimizer, usual convergence and regularization results from the continuous setting can be recovered. As a matter of fact, it is shown that it suffices to use stationary points of the Tikhonov functional. The efficiency of the proposed method is demonstrated by means of numerical experiments. (paper)
A distributed approach for parameters estimation in System Biology models
International Nuclear Information System (INIS)
Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.
2009-01-01
Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.
Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation
2016-08-29
In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.
Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation
Unknown author
2016-01-01
In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.
Multivariate phase type distributions - Applications and parameter estimation
DEFF Research Database (Denmark)
Meisch, David
The best known univariate probability distribution is the normal distribution. It is used throughout the literature in a broad field of applications. In cases where it is not sensible to use the normal distribution alternative distributions are at hand and well understood, many of these belonging...... and statistical inference, is the multivariate normal distribution. Unfortunately only little is known about the general class of multivariate phase type distribution. Considering the results concerning parameter estimation and inference theory of univariate phase type distributions, the class of multivariate...... projects and depend on reliable cost estimates. The Successive Principle is a group analysis method primarily used for analyzing medium to large projects in relation to cost or duration. We believe that the mathematical modeling used in the Successive Principle can be improved. We suggested a novel...
Estimation of modal parameters using bilinear joint time frequency distributions
Roshan-Ghias, A.; Shamsollahi, M. B.; Mobed, M.; Behzad, M.
2007-07-01
In this paper, a new method is proposed for modal parameter estimation using time-frequency representations. Smoothed Pseudo Wigner-Ville distribution which is a member of the Cohen's class distributions is used to decouple vibration modes completely in order to study each mode separately. This distribution reduces cross-terms which are troublesome in Wigner-Ville distribution and retains the resolution as well. The method was applied to highly damped systems, and results were superior to those obtained via other conventional methods.
Distributed control design for nonlinear output agreement in convergent systems
Weitenberg, Erik; De Persis, Claudio
2015-01-01
This work studies the problem of output agreement in homogeneous networks of nonlinear dynamical systems under time-varying disturbances using controllers placed at the nodes of the networks. For the class of contractive systems, necessary and sufficient conditions for output agreement are derived,
Hamim, Salah Uddin Ahmed
Nanoindentation involves probing a hard diamond tip into a material, where the load and the displacement experienced by the tip is recorded continuously. This load-displacement data is a direct function of material's innate stress-strain behavior. Thus, theoretically it is possible to extract mechanical properties of a material through nanoindentation. However, due to various nonlinearities associated with nanoindentation the process of interpreting load-displacement data into material properties is difficult. Although, simple elastic behavior can be characterized easily, a method to characterize complicated material behavior such as nonlinear viscoelasticity is still lacking. In this study, a nanoindentation-based material characterization technique is developed to characterize soft materials exhibiting nonlinear viscoelasticity. Nanoindentation experiment was modeled in finite element analysis software (ABAQUS), where a nonlinear viscoelastic behavior was incorporated using user-defined subroutine (UMAT). The model parameters were calibrated using a process called inverse analysis. In this study, a surrogate model-based approach was used for the inverse analysis. The different factors affecting the surrogate model performance are analyzed in order to optimize the performance with respect to the computational cost.
Determination of the Nonlinearity Parameter in the TNM Model of Structural Recovery
Bari, Rozana; Simon, Sindee
Structural recovery of non-equilibrium glassy materials takes place by evolution of volume and enthalpy as the glass attempts to reach to equilibrium. Structural recovery is nonlinear, nonexponential, and depends on thermal history and the process can be described by phenomenological models of structural recovery, such as the Tool-Narayanaswamy-Moynihan (TNM) and the Kovacs-Aklonis-Hutchinson-Ramos (KAHR) models. The goal of the present work is to analyze methods to determine the nonlinearity parameter x and activation energy Δh/R. The methods to determine x includes the inflectional analysis, time-temperature superposition, and two-step temperature jump methods. The activation energy Δh/R can also be obtained by the first two methods. The TNM model is used to simulate structural recovery data, which are then used to test the accuracy of the methods to determine x and Δh/R, with a particular interest in data obtained after cooling at high rates as can be obtained in the Flash DSC. The nonlinearity parameter x by the inflectional analysis and two-step temperature methods are accurate for exponential recovery. However, for real systems with nonexponential relaxation, methods to determine x are not reliable. The activation energy is well estimated by both the time-temperature superposition and inflectional analysis methods, with the former being slightly better.
Ganji, S. S.; Domairry, G.; Davodi, A. G.; Babazadeh, H.; Seyedalizadeh Ganji, S. H.
The main objective of this paper is to apply the parameter expansion technique (a modified Lindstedt-Poincaré method) to calculate the first, second, and third-order approximations of motion of a nonlinear oscillator arising in rigid rod rocking back. The dynamics and frequency of motion of this nonlinear mechanical system are analyzed. A meticulous attention is carried out to the study of the introduced nonlinearity effects on the amplitudes of the oscillatory states and on the bifurcation structures. We examine the synchronization and the frequency of systems using both the strong and special method. Numerical simulations and computer's answers confirm and complement the results obtained by the analytical approach. The approach proposes a choice to overcome the difficulty of computing the periodic behavior of the oscillation problems in engineering. The solutions of this method are compared with the exact ones in order to validate the approach, and assess the accuracy of the solutions. In particular, APL-PM works well for the whole range of oscillation amplitudes and excellent agreement of the approximate frequency with the exact one has been demonstrated. The approximate period derived here is accurate and close to the exact solution. This method has a distinguished feature which makes it simple to use, and also it agrees with the exact solutions for various parameters.
Directory of Open Access Journals (Sweden)
Dan Selişteanu
2015-01-01
Full Text Available Monoclonal antibodies (mAbs are at present one of the fastest growing products of pharmaceutical industry, with widespread applications in biochemistry, biology, and medicine. The operation of mAbs production processes is predominantly based on empirical knowledge, the improvements being achieved by using trial-and-error experiments and precedent practices. The nonlinearity of these processes and the absence of suitable instrumentation require an enhanced modelling effort and modern kinetic parameter estimation strategies. The present work is dedicated to nonlinear dynamic modelling and parameter estimation for a mammalian cell culture process used for mAb production. By using a dynamical model of such kind of processes, an optimization-based technique for estimation of kinetic parameters in the model of mammalian cell culture process is developed. The estimation is achieved as a result of minimizing an error function by a particle swarm optimization (PSO algorithm. The proposed estimation approach is analyzed in this work by using a particular model of mammalian cell culture, as a case study, but is generic for this class of bioprocesses. The presented case study shows that the proposed parameter estimation technique provides a more accurate simulation of the experimentally observed process behaviour than reported in previous studies.
Romanelli, N.; Mazelle, C.; Meziane, K.
2018-02-01
Seen from the solar wind (SW) reference frame, the presence of newborn planetary protons upstream from the Martian and Venusian bow shocks and SW protons reflected from each of them constitutes two sources of nonthermal proton populations. In both cases, the resulting proton velocity distribution function is highly unstable and capable of giving rise to ultralow frequency quasi-monochromatic electromagnetic plasma waves. When these instabilities take place, the resulting nonlinear waves are convected by the SW and interact with nonthermal protons located downstream from the wave generation region (upstream from the bow shock), playing a predominant role in their dynamics. To improve our understanding of these phenomena, we study the interaction between a charged particle and a large-amplitude monochromatic circularly polarized electromagnetic wave propagating parallel to a background magnetic field, from first principles. We determine the number of fix points in velocity space, their stability, and their dependence on different wave-particle parameters. Particularly, we determine the temporal evolution of a charged particle in the pitch angle-gyrophase velocity plane under nominal conditions expected for backstreaming protons in planetary foreshocks and for newborn planetary protons in the upstream regions of Venus and Mars. In addition, the inclusion of wave ellipticity effects provides an explanation for pitch angle distributions of suprathermal protons observed at the Earth's foreshock, reported in previous studies. These analyses constitute a mean to evaluate if nonthermal proton velocity distribution functions observed at these plasma environments present signatures that can be understood in terms of nonlinear wave-particle processes.
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
Directory of Open Access Journals (Sweden)
V. Rajinikanth
2012-01-01
Full Text Available An enhanced bacteria foraging optimization (EBFO algorithm-based Proportional + integral + derivative (PID controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.
Automated detection of sleep apnea from electrocardiogram signals using nonlinear parameters
International Nuclear Information System (INIS)
Acharya, U Rajendra; Faust, Oliver; Chua, Eric Chern-Pin; Lim, Teik-Cheng; Lim, Liang Feng Benjamin
2011-01-01
Sleep apnoea is a very common sleep disorder which can cause symptoms such as daytime sleepiness, irritability and poor concentration. To monitor patients with this sleeping disorder we measured the electrical activity of the heart. The resulting electrocardiography (ECG) signals are both non-stationary and nonlinear. Therefore, we used nonlinear parameters such as approximate entropy, fractal dimension, correlation dimension, largest Lyapunov exponent and Hurst exponent to extract physiological information. This information was used to train an artificial neural network (ANN) classifier to categorize ECG signal segments into one of the following groups: apnoea, hypopnoea and normal breathing. ANN classification tests produced an average classification accuracy of 90%; specificity and sensitivity were 100% and 95%, respectively. We have also proposed unique recurrence plots for the normal, hypopnea and apnea classes. Detecting sleep apnea with this level of accuracy can potentially reduce the need of polysomnography (PSG). This brings advantages to patients, because the proposed system is less cumbersome when compared to PSG
Beyer's non-linearity parameter (B/A) in benzylidene aniline Schiff base liquid crystalline systems
International Nuclear Information System (INIS)
Nagi Reddy, M.V.V.; Pisipati, V.G.K.M.; Madhavi Latha, D.; Datta Prasad, P.V.
2011-01-01
The non-linearity parameter B/A is estimated for a number of liquid crystal materials of the type N-(p-n-alkoxy benzylidene)-p-n-alkyl anilines, popularly known as nO.m, where n and m are the aliphatic chains on either side of the rigid core, which can be varied from 1 to 18 to realize a number of LC materials with a variety LC phase variants. The B/A values are computed from both density and sound velocity data following standard relations reported in literature. This systematic study in a homologous series provides an opportunity to study how this parameter behaves with (1) either the alkoxy and/or alkyl chain number, (2) with the total chain number (n+m), (3) with increase in molecular weight and (4) whether the linear relations reported in literature either with αT [thermal expansion coefficient (α) and temperature (T)] and sound velocity (u) will hold good or not and if so to what extent. The results are discussed with the body of data available in literature on liquids, liquid mixtures and other LC materials. -- Research highlights: → The Bayer's non-linearity parameter (B/A) is estimated for the first time for a number liquid crystal materials of the type N-(p-n-alkoxy benzylidene)-p-nalkyl anilines. → The magnitude of B/A estimated from sound velocity data is higher compared to that estimated thermal expansion data. → The B/A value decreases with increase in molecular weight with an even odd fashion and reaches a minimum value and saturates. → These studies reveal that both the thermal expansion coefficient and sound velocity are the tools to estimate the non-linear parameter B/A in the case of liquid crystals.
The Power of Heterogeneity: Parameter Relationships from Distributions
Röding, Magnus; Bradley, Siobhan J.; Williamson, Nathan H.; Dewi, Melissa R.; Nann, Thomas; Nydén, Magnus
2016-01-01
Complex scientific data is becoming the norm, many disciplines are growing immensely data-rich, and higher-dimensional measurements are performed to resolve complex relationships between parameters. Inherently multi-dimensional measurements can directly provide information on both the distributions of individual parameters and the relationships between them, such as in nuclear magnetic resonance and optical spectroscopy. However, when data originates from different measurements and comes in different forms, resolving parameter relationships is a matter of data analysis rather than experiment. We present a method for resolving relationships between parameters that are distributed individually and also correlated. In two case studies, we model the relationships between diameter and luminescence properties of quantum dots and the relationship between molecular weight and diffusion coefficient for polymers. Although it is expected that resolving complicated correlated relationships require inherently multi-dimensional measurements, our method constitutes a useful contribution to the modelling of quantitative relationships between correlated parameters and measurements. We emphasise the general applicability of the method in fields where heterogeneity and complex distributions of parameters are obstacles to scientific insight. PMID:27182701
Nonlinear control of linear parameter varying systems with applications to hypersonic vehicles
Wilcox, Zachary Donald
The focus of this dissertation is to design a controller for linear parameter varying (LPV) systems, apply it specifically to air-breathing hypersonic vehicles, and examine the interplay between control performance and the structural dynamics design. Specifically a Lyapunov-based continuous robust controller is developed that yields exponential tracking of a reference model, despite the presence of bounded, nonvanishing disturbances. The hypersonic vehicle has time varying parameters, specifically temperature profiles, and its dynamics can be reduced to an LPV system with additive disturbances. Since the HSV can be modeled as an LPV system the proposed control design is directly applicable. The control performance is directly examined through simulations. A wide variety of applications exist that can be effectively modeled as LPV systems. In particular, flight systems have historically been modeled as LPV systems and associated control tools have been applied such as gain-scheduling, linear matrix inequalities (LMIs), linear fractional transformations (LFT), and mu-types. However, as the type of flight environments and trajectories become more demanding, the traditional LPV controllers may no longer be sufficient. In particular, hypersonic flight vehicles (HSVs) present an inherently difficult problem because of the nonlinear aerothermoelastic coupling effects in the dynamics. HSV flight conditions produce temperature variations that can alter both the structural dynamics and flight dynamics. Starting with the full nonlinear dynamics, the aerothermoelastic effects are modeled by a temperature dependent, parameter varying state-space representation with added disturbances. The model includes an uncertain parameter varying state matrix, an uncertain parameter varying non-square (column deficient) input matrix, and an additive bounded disturbance. In this dissertation, a robust dynamic controller is formulated for a uncertain and disturbed LPV system. The developed
A Semismooth Newton Method for Nonlinear Parameter Identification Problems with Impulsive Noise
Clason, Christian
2012-01-01
This work is concerned with nonlinear parameter identification in partial differential equations subject to impulsive noise. To cope with the non-Gaussian nature of the noise, we consider a model with L 1 fitting. However, the nonsmoothness of the problem makes its efficient numerical solution challenging. By approximating this problem using a family of smoothed functionals, a semismooth Newton method becomes applicable. In particular, its superlinear convergence is proved under a second-order condition. The convergence of the solution to the approximating problem as the smoothing parameter goes to zero is shown. A strategy for adaptively selecting the regularization parameter based on a balancing principle is suggested. The efficiency of the method is illustrated on several benchmark inverse problems of recovering coefficients in elliptic differential equations, for which one- and two-dimensional numerical examples are presented. © by SIAM.
Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan
2015-02-01
The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.
Directory of Open Access Journals (Sweden)
Jeng-Wen Lin
2009-01-01
Full Text Available This paper proposes a statistical confidence interval based nonlinear model parameter refinement approach for the health monitoring of structural systems subjected to seismic excitations. The developed model refinement approach uses the 95% confidence interval of the estimated structural parameters to determine their statistical significance in a least-squares regression setting. When the parameters' confidence interval covers the zero value, it is statistically sustainable to truncate such parameters. The remaining parameters will repetitively undergo such parameter sifting process for model refinement until all the parameters' statistical significance cannot be further improved. This newly developed model refinement approach is implemented for the series models of multivariable polynomial expansions: the linear, the Taylor series, and the power series model, leading to a more accurate identification as well as a more controllable design for system vibration control. Because the statistical regression based model refinement approach is intrinsically used to process a “batch” of data and obtain an ensemble average estimation such as the structural stiffness, the Kalman filter and one of its extended versions is introduced to the refined power series model for structural health monitoring.
International Nuclear Information System (INIS)
Rao, N.N.
1998-01-01
A systematic analysis of the stationary propagation of nonlinearly coupled electromagnetic and ion-acoustic waves in an unmagnetized plasma via the ponderomotive force is carried out. For small but finite amplitudes, the governing equations have a Hamiltonian structure, but with a kinetic energy term that is not positive definite. The Hamiltonian is similar to the well-known Hacute enon endash Heiles Hamiltonian of nonlinear dynamics, and is completely integrable in three regimes of the allowed parameter space. The corresponding second invariants of motion are also explicitly obtained. The integrable parameter regimes correspond to supersonic values of the Mach number, which characterizes the propagation speed of the coupled waves. On the other hand, in the sub- as well as near-sonic regimes, the coupled mode equations admit different types of exact analytical solutions, which represent nonlinear localized eigenstates of the electromagnetic field trapped in the density cavity due to the ponderomotive potential. While the density cavity has always a single-dip structure, for larger amplitudes it can support higher-order modes having a larger number of nodes in the electromagnetic field. In particular, we show the existence of a new type of localized electromagnetic wave whose field intensity has a triple-hump structure. For typical parameter values, the triple-hump solitons propagate with larger Mach numbers that are closer to the sonic limit than the single- as well as the double-hump solitons, but carry a lesser amount of the electromagnetic field energy. A comparison between the different types of solutions is carried out. The possibility of the existence of trapped electromagnetic modes having a larger number of humps is also discussed. copyright 1998 American Institute of Physics
Adaptive distributed parameter and input estimation in linear parabolic PDEs
Mechhoud, Sarra
2016-01-01
In this paper, we discuss the on-line estimation of distributed source term, diffusion, and reaction coefficients of a linear parabolic partial differential equation using both distributed and interior-point measurements. First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.
The optimization of the nonlinear parameters in the transcorrelated method: the hydrogen molecule
International Nuclear Information System (INIS)
Huggett, J.P.; Armour, E.A.G.
1976-01-01
The nonlinear parameters in a transcorrelated calculation of the groundstate energy and wavefunction of the hydrogen molecule are optimized using the method of Boys and Handy (Proc. R. Soc. A.; 309:195 and 209, 310:43 and 63, 311:309 (1969)). The method gives quite accurate results in all cases and in some cases the results are highly accurate. This is the first time the method has been applied to the optimization of a term in the correlation function which depends linearly on the interelectronic distance. (author)
Determination of power system component parameters using nonlinear dead beat estimation method
Kolluru, Lakshmi
Power systems are considered the most complex man-made wonders in existence today. In order to effectively supply the ever increasing demands of the consumers, power systems are required to remain stable at all times. Stability and monitoring of these complex systems are achieved by strategically placed computerized control centers. State and parameter estimation is an integral part of these facilities, as they deal with identifying the unknown states and/or parameters of the systems. Advancements in measurement technologies and the introduction of phasor measurement units (PMU) provide detailed and dynamic information of all measurements. Accurate availability of dynamic measurements provides engineers the opportunity to expand and explore various possibilities in power system dynamic analysis/control. This thesis discusses the development of a parameter determination algorithm for nonlinear power systems, using dynamic data obtained from local measurements. The proposed algorithm was developed by observing the dead beat estimator used in state space estimation of linear systems. The dead beat estimator is considered to be very effective as it is capable of obtaining the required results in a fixed number of steps. The number of steps required is related to the order of the system and the number of parameters to be estimated. The proposed algorithm uses the idea of dead beat estimator and nonlinear finite difference methods to create an algorithm which is user friendly and can determine the parameters fairly accurately and effectively. The proposed algorithm is based on a deterministic approach, which uses dynamic data and mathematical models of power system components to determine the unknown parameters. The effectiveness of the algorithm is tested by implementing it to identify the unknown parameters of a synchronous machine. MATLAB environment is used to create three test cases for dynamic analysis of the system with assumed known parameters. Faults are
Linear and nonlinear ARMA model parameter estimation using an artificial neural network
Chon, K. H.; Cohen, R. J.
1997-01-01
This paper addresses parametric system identification of linear and nonlinear dynamic systems by analysis of the input and output signals. Specifically, we investigate the relationship between estimation of the system using a feedforward neural network model and estimation of the system by use of linear and nonlinear autoregressive moving-average (ARMA) models. By utilizing a neural network model incorporating a polynomial activation function, we show the equivalence of the artificial neural network to the linear and nonlinear ARMA models. We compare the parameterization of the estimated system using the neural network and ARMA approaches by utilizing data generated by means of computer simulations. Specifically, we show that the parameters of a simulated ARMA system can be obtained from the neural network analysis of the simulated data or by conventional least squares ARMA analysis. The feasibility of applying neural networks with polynomial activation functions to the analysis of experimental data is explored by application to measurements of heart rate (HR) and instantaneous lung volume (ILV) fluctuations.
Discrete- and finite-bandwidth-frequency distributions in nonlinear stability applications
Kuehl, Joseph J.
2017-02-01
A new "wave packet" formulation of the parabolized stability equations method is presented. This method accounts for the influence of finite-bandwidth-frequency distributions on nonlinear stability calculations. The methodology is motivated by convolution integrals and is found to appropriately represent nonlinear energy transfer between primary modes and harmonics, in particular nonlinear feedback, via a "nonlinear coupling coefficient." It is found that traditional discrete mode formulations overestimate nonlinear feedback by approximately 70%. This results in smaller maximum disturbance amplitudes than those observed experimentally. The new formulation corrects this overestimation, accounts for the generation of side lobes responsible for spectral broadening, and results in disturbance representation more consistent with the experiment than traditional formulations. A Mach 6 flared-cone example is presented.
Iterative methods for distributed parameter estimation in parabolic PDE
Energy Technology Data Exchange (ETDEWEB)
Vogel, C.R. [Montana State Univ., Bozeman, MT (United States); Wade, J.G. [Bowling Green State Univ., OH (United States)
1994-12-31
The goal of the work presented is the development of effective iterative techniques for large-scale inverse or parameter estimation problems. In this extended abstract, a detailed description of the mathematical framework in which the authors view these problem is presented, followed by an outline of the ideas and algorithms developed. Distributed parameter estimation problems often arise in mathematical modeling with partial differential equations. They can be viewed as inverse problems; the `forward problem` is that of using the fully specified model to predict the behavior of the system. The inverse or parameter estimation problem is: given the form of the model and some observed data from the system being modeled, determine the unknown parameters of the model. These problems are of great practical and mathematical interest, and the development of efficient computational algorithms is an active area of study.
Statistical distributions of earthquakes and related non-linear features in seismic waves
International Nuclear Information System (INIS)
Apostol, B.-F.
2006-01-01
A few basic facts in the science of the earthquakes are briefly reviewed. An accumulation, or growth, model is put forward for the focal mechanisms and the critical focal zone of the earthquakes, which relates the earthquake average recurrence time to the released seismic energy. The temporal statistical distribution for average recurrence time is introduced for earthquakes, and, on this basis, the Omori-type distribution in energy is derived, as well as the distribution in magnitude, by making use of the semi-empirical Gutenberg-Richter law relating seismic energy to earthquake magnitude. On geometric grounds, the accumulation model suggests the value r = 1/3 for the Omori parameter in the power-law of energy distribution, which leads to β = 1,17 for the coefficient in the Gutenberg-Richter recurrence law, in fair agreement with the statistical analysis of the empirical data. Making use of this value, the empirical Bath's law is discussed for the average magnitude of the aftershocks (which is 1.2 less than the magnitude of the main seismic shock), by assuming that the aftershocks are relaxation events of the seismic zone. The time distribution of the earthquakes with a fixed average recurrence time is also derived, the earthquake occurrence prediction is discussed by means of the average recurrence time and the seismicity rate, and application of this discussion to the seismic region Vrancea, Romania, is outlined. Finally, a special effect of non-linear behaviour of the seismic waves is discussed, by describing an exact solution derived recently for the elastic waves equation with cubic anharmonicities, its relevance, and its connection to the approximate quasi-plane waves picture. The properties of the seismic activity accompanying a main seismic shock, both like foreshocks and aftershocks, are relegated to forthcoming publications. (author)
Albert, Carlo; Ulzega, Simone; Stoop, Ruedi
2016-04-01
Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.
Self-similar optical pulses in competing cubic-quintic nonlinear media with distributed coefficients
International Nuclear Information System (INIS)
Zhang Jiefang; Tian Qing; Wang Yueyue; Dai Chaoqing; Wu Lei
2010-01-01
We present a systematic analysis of the self-similar propagation of optical pulses within the framework of the generalized cubic-quintic nonlinear Schroedinger equation with distributed coefficients. By appropriately choosing the relations between the distributed coefficients, we not only retrieve the exact self-similar solitonic solutions, but also find both the approximate self-similar Gaussian-Hermite solutions and compact solutions. Our analytical and numerical considerations reveal that proper choices of the distributed coefficients could make the unstable solitons stable and could restrict the nonlinear interaction between the neighboring solitons.
Three types magnetic moment distribution of nonlinear excitations in a Heisenberg helimagnet
Energy Technology Data Exchange (ETDEWEB)
Qi, Jian-Wen [School of Physics, Northwest University, Xi' an 710069 (China); Shaanxi Key Laboratory for Theoretical Physics Frontiers, Xi' an 710069 (China); Li, Zai-Dong [Department of Applied Physics, Hebei University of Technology, Tianjin 300401 (China); Yang, Zhan-Ying, E-mail: zyyang@nwu.edu.cn [School of Physics, Northwest University, Xi' an 710069 (China); Shaanxi Key Laboratory for Theoretical Physics Frontiers, Xi' an 710069 (China); Yang, Wen-Li [Shaanxi Key Laboratory for Theoretical Physics Frontiers, Xi' an 710069 (China); Institute of Modern Physics, Northwest University, Xi' an 710069 (China)
2017-06-15
Highlights: • Three different types of soliton excitations under the spin-wave background are demonstrated in spin chain system. • The magnetic moment distributions corresponding to these solitons are characterized in detail. • The formation mechanisms of those excitations are explained by the magnon density distribution. - Abstract: We study the nonlinear spin dynamics of an anisotropic Heisenberg helimagnet in a fourth-order integrable nonlinear Schrödinger equation. We demonstrate that there are three types of nonlinear spin excitations on a spin-wave background in the Heisenberg helimagnet, notably including anti-dark soliton, W-shaped soliton, and multi-peak soliton. The magnetic moment distribution that corresponds to each of these are characterized in detail. Additionally, the formation mechanism is clarified by the magnon density distribution.
Miksovsky, J.; Raidl, A.
Time delays phase space reconstruction represents one of useful tools of nonlinear time series analysis, enabling number of applications. Its utilization requires the value of time delay to be known, as well as the value of embedding dimension. There are sev- eral methods how to estimate both these parameters. Typically, time delay is computed first, followed by embedding dimension. Our presented approach is slightly different - we reconstructed phase space for various combinations of mentioned parameters and used it for prediction by means of the nearest neighbours in the phase space. Then some measure of prediction's success was computed (correlation or RMSE, e.g.). The position of its global maximum (minimum) should indicate the suitable combination of time delay and embedding dimension. Several meteorological (particularly clima- tological) time series were used for the computations. We have also created a MS- Windows based program in order to implement this approach - its basic features will be presented as well.
DEFF Research Database (Denmark)
Chon, K H; Hoyer, D; Armoundas, A A
1999-01-01
In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic...... part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction...... error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate...
An, Honglin; Fleming, Simon
2005-05-02
The spatial distribution of second-order nonlinearity in thermally poled optical fibers was characterized by second-harmonic microscopy. The second-order nonlinearity was found to be confined to a thin layer close to the anode surface and progressed further into the silica as the poling time increased. Position uncertainty of the anode metal wire was observed to have an effect, as the nonlinear layers were found not always symmetrically located around the nearest points between the anode and cathode. Optical microscopy results were obtained on etched poled fiber cross-sections and compared with those from second-harmonic microscopy.
Two-parameter nonlinear spacetime perturbations: gauge transformations and gauge invariance
International Nuclear Information System (INIS)
Bruni, Marco; Gualtieri, Leonardo; Sopuerta, Carlos F
2003-01-01
An implicit fundamental assumption in relativistic perturbation theory is that there exists a parametric family of spacetimes that can be Taylor expanded around a background. The choice of the latter is crucial to obtain a manageable theory, so that it is sometime convenient to construct a perturbative formalism based on two (or more) parameters. The study of perturbations of rotating stars is a good example: in this case one can treat the stationary axisymmetric star using a slow rotation approximation (expansion in the angular velocity Ω), so that the background is spherical. Generic perturbations of the rotating star (say parametrized by λ) are then built on top of the axisymmetric perturbations in Ω. Clearly, any interesting physics requires nonlinear perturbations, as at least terms λΩ need to be considered. In this paper, we analyse the gauge dependence of nonlinear perturbations depending on two parameters, derive explicit higher-order gauge transformation rules and define gauge invariance. The formalism is completely general and can be used in different applications of general relativity or any other spacetime theory
Evaluation of unconfined-aquifer parameters from pumping test data by nonlinear least squares
Heidari, Manoutchehr; Wench, Allen
1997-05-01
Nonlinear least squares (NLS) with automatic differentiation was used to estimate aquifer parameters from drawdown data obtained from published pumping tests conducted in homogeneous, water-table aquifers. The method is based on a technique that seeks to minimize the squares of residuals between observed and calculated drawdown subject to bounds that are placed on the parameter of interest. The analytical model developed by Neuman for flow to a partially penetrating well of infinitesimal diameter situated in an infinite, homogeneous and anisotropic aquifer was used to obtain calculated drawdown. NLS was first applied to synthetic drawdown data from a hypothetical but realistic aquifer to demonstrate that the relevant hydraulic parameters (storativity, specific yield, and horizontal and vertical hydraulic conductivity) can be evaluated accurately. Next the method was used to estimate the parameters at three field sites with widely varying hydraulic properties. NLS produced unbiased estimates of the aquifer parameters that are close to the estimates obtained with the same data using a visual curve-matching approach. Small differences in the estimates are a consequence of subjective interpretation introduced in the visual approach.
Weakly intrusive low-rank approximation method for nonlinear parameter-dependent equations
Giraldi, Loic; Nouy, Anthony
2017-01-01
This paper presents a weakly intrusive strategy for computing a low-rank approximation of the solution of a system of nonlinear parameter-dependent equations. The proposed strategy relies on a Newton-like iterative solver which only requires evaluations of the residual of the parameter-dependent equation and of a preconditioner (such as the differential of the residual) for instances of the parameters independently. The algorithm provides an approximation of the set of solutions associated with a possibly large number of instances of the parameters, with a computational complexity which can be orders of magnitude lower than when using the same Newton-like solver for all instances of the parameters. The reduction of complexity requires efficient strategies for obtaining low-rank approximations of the residual, of the preconditioner, and of the increment at each iteration of the algorithm. For the approximation of the residual and the preconditioner, weakly intrusive variants of the empirical interpolation method are introduced, which require evaluations of entries of the residual and the preconditioner. Then, an approximation of the increment is obtained by using a greedy algorithm for low-rank approximation, and a low-rank approximation of the iterate is finally obtained by using a truncated singular value decomposition. When the preconditioner is the differential of the residual, the proposed algorithm is interpreted as an inexact Newton solver for which a detailed convergence analysis is provided. Numerical examples illustrate the efficiency of the method.
Weakly intrusive low-rank approximation method for nonlinear parameter-dependent equations
Giraldi, Loic
2017-06-30
This paper presents a weakly intrusive strategy for computing a low-rank approximation of the solution of a system of nonlinear parameter-dependent equations. The proposed strategy relies on a Newton-like iterative solver which only requires evaluations of the residual of the parameter-dependent equation and of a preconditioner (such as the differential of the residual) for instances of the parameters independently. The algorithm provides an approximation of the set of solutions associated with a possibly large number of instances of the parameters, with a computational complexity which can be orders of magnitude lower than when using the same Newton-like solver for all instances of the parameters. The reduction of complexity requires efficient strategies for obtaining low-rank approximations of the residual, of the preconditioner, and of the increment at each iteration of the algorithm. For the approximation of the residual and the preconditioner, weakly intrusive variants of the empirical interpolation method are introduced, which require evaluations of entries of the residual and the preconditioner. Then, an approximation of the increment is obtained by using a greedy algorithm for low-rank approximation, and a low-rank approximation of the iterate is finally obtained by using a truncated singular value decomposition. When the preconditioner is the differential of the residual, the proposed algorithm is interpreted as an inexact Newton solver for which a detailed convergence analysis is provided. Numerical examples illustrate the efficiency of the method.
International Nuclear Information System (INIS)
Civalek, Ö.
2014-01-01
In the present study nonlinear static and dynamic responses of shallow spherical shells resting on Winkler–Pasternak elastic foundations are carried out. The formulation of the shells is based on the Donnell theory. The nonlinear governing equations of motion of shallow shells are discretized in space and time domains using the discrete singular convolution and the differential quadrature methods, respectively. The validity of the present method is demonstrated by comparing the present results with those available in the open literature. The effects of the Winkler and Pasternak foundation parameters on nonlinear static and dynamic response of shells are investigated. Some results are also presented for circular plate as special case. Damping effect on nonlinear dynamic response of shells is studied. It is important to state that the increase in damping parameter causes decrease in the dynamic response of the shells. It is shown that the shear parameter of the foundation has a significant influence on the dynamic and static response of the shells. Also, the response of the shell is decreased with the increasing value of the shear parameter of the foundation. Parametric studies considering different geometric variables have also been investigated. -- Highlights: • Nonlinear responses of shallow spherical shells are presented. • The effects of foundation parameters are investigated. • Damping effect on nonlinear dynamic response of shells is also studied
International Nuclear Information System (INIS)
Belmonte-Beitia, Juan; Konotop, Vladimir V.; Perez-Garcia, Victor M.; Vekslerchik, Vadym E.
2009-01-01
Using similarity transformations we construct explicit solutions of the nonlinear Schroedinger equation with linear and nonlinear periodic potentials. We present explicit forms of spatially localized and periodic solutions, and study their properties. We put our results in the framework of the exploited perturbation techniques and discuss their implications on the properties of associated linear periodic potentials and on the possibilities of stabilization of gap solitons using polychromatic lattices.
Reservoir theory, groundwater transit time distributions, and lumped parameter models
International Nuclear Information System (INIS)
Etcheverry, D.; Perrochet, P.
1999-01-01
The relation between groundwater residence times and transit times is given by the reservoir theory. It allows to calculate theoretical transit time distributions in a deterministic way, analytically, or on numerical models. Two analytical solutions validates the piston flow and the exponential model for simple conceptual flow systems. A numerical solution of a hypothetical regional groundwater flow shows that lumped parameter models could be applied in some cases to large-scale, heterogeneous aquifers. (author)
Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel
2016-01-01
Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization.
Global Distribution Adjustment and Nonlinear Feature Transformation for Automatic Colorization
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Terumasa Aoki
2018-01-01
Full Text Available Automatic colorization is generally classified into two groups: propagation-based methods and reference-based methods. In reference-based automatic colorization methods, color image(s are used as reference(s to reconstruct original color of a gray target image. The most important task here is to find the best matching pairs for all pixels between reference and target images in order to transfer color information from reference to target pixels. A lot of attractive local feature-based image matching methods have already been developed for the last two decades. Unfortunately, as far as we know, there are no optimal matching methods for automatic colorization because the requirements for pixel matching in automatic colorization are wholly different from those for traditional image matching. To design an efficient matching algorithm for automatic colorization, clustering pixel with low computational cost and generating descriptive feature vector are the most important challenges to be solved. In this paper, we present a novel method to address these two problems. In particular, our work concentrates on solving the second problem (designing a descriptive feature vector; namely, we will discuss how to learn a descriptive texture feature using scaled sparse texture feature combining with a nonlinear transformation to construct an optimal feature descriptor. Our experimental results show our proposed method outperforms the state-of-the-art methods in terms of robustness for color reconstruction for automatic colorization applications.
Distributed Fuzzy and Stochastic Observers for Nonlinear Systems
Lendek, Z.
2009-01-01
Many problems in decision making, control, and monitoring require that all variables of interest, usually states and parameters of the system, are known at all times. However, in practical situations, not all variables are measurable or they are not measured due to technical or economical reasons.
Nonlinear systems time-varying parameter estimation: Application to induction motors
Energy Technology Data Exchange (ETDEWEB)
Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)
2008-11-15
In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)
An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.
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Afnizanfaizal Abdullah
Full Text Available The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.
An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.
Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V
2013-01-01
The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.
Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection.
Wang, Xinghu; Hong, Yiguang; Ji, Haibo
2016-07-01
The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.
Institute of Scientific and Technical Information of China (English)
Zaiyu; Chen; Minghui; Yin; Lianjun; Zhou; Yaping; Xia; Jiankun; Liu; Yun; Zou
2017-01-01
Since mechanical loads exert a significant influence on the life span of wind turbines, the reduction of transient load on drive-train shaft has received more attention when implementing a maximum power point tracking(MPPT) controller.Moreover, a trade-off between the efficiency of wind energy extraction and the load level of drive-train shaft becomes a key issue. However, for the existing control strategies based on nonlinear model of wind turbines, the MPPT efficiencies are improved at the cost of the intensive fluctuation of generator torque and significant increase of transient load on drive train shaft. Hence, in this paper, a nonlinear controller with variable parameter is proposed for improving MPPT efficiency and mitigating transient load on drive-train simultaneously. Then,simulations on FAST(Fatigue, Aerodynamics, Structures, and Turbulence) code and experiments on the wind turbine simulator(WTS) based test bench are presented to verify the efficiency improvement of the proposed control strategy with less cost of drive-train load.
Institute of Scientific and Technical Information of China (English)
Zaiyu Chen; Minghui Yin; Lianjun Zhou; Yaping Xia; Jiankun Liu; Yun Zou
2017-01-01
Since mechanical loads exert a significant influence on the life span of wind turbines,the reduction of transient load on drive-train shaft has received more attention when implementing a maximum power point tracking (MPPT) controller.Moreover,a trade-off between the efficiency of wind energy extraction and the load level of drive-train shaft becomes a key issue.However,for the existing control strategies based on nonlinear model of wind turbines,the MPPT efficiencies are improved at the cost of the intensive fluctuation of generator torque and significant increase of transient load on drive train shaft.Hence,in this paper,a nonlinear controller with variable parameter is proposed for improving MPPT efficiency and mitigating transient load on drive-train simultaneously.Then,simulations on FAST (Fatigue,Aerodynamics,Structures,and Turbulence) code and experiments on the wind turbine simulator (WTS) based test bench are presented to verify the efficiency improvement of the proposed control strategy with less cost of drive-train load.
Confidence limits for parameters of Poisson and binomial distributions
International Nuclear Information System (INIS)
Arnett, L.M.
1976-04-01
The confidence limits for the frequency in a Poisson process and for the proportion of successes in a binomial process were calculated and tabulated for the situations in which the observed values of the frequency or proportion and an a priori distribution of these parameters are available. Methods are used that produce limits with exactly the stated confidence levels. The confidence interval [a,b] is calculated so that Pr [a less than or equal to lambda less than or equal to b c,μ], where c is the observed value of the parameter, and μ is the a priori hypothesis of the distribution of this parameter. A Bayesian type analysis is used. The intervals calculated are narrower and appreciably different from results, known to be conservative, that are often used in problems of this type. Pearson and Hartley recognized the characteristics of their methods and contemplated that exact methods could someday be used. The calculation of the exact intervals requires involved numerical analyses readily implemented only on digital computers not available to Pearson and Hartley. A Monte Carlo experiment was conducted to verify a selected interval from those calculated. This numerical experiment confirmed the results of the analytical methods and the prediction of Pearson and Hartley that their published tables give conservative results
International Nuclear Information System (INIS)
Jeong, Hyunjo; Zhang, Shuzeng; Li, Xiongbing; Barnard, Dan
2015-01-01
The accurate measurement of acoustic nonlinearity parameter β for fluids or solids generally requires making corrections for diffraction effects due to finite size geometry of transmitter and receiver. These effects are well known in linear acoustics, while those for second harmonic waves have not been well addressed and therefore not properly considered in previous studies. In this work, we explicitly define the attenuation and diffraction corrections using the multi-Gaussian beam (MGB) equations which were developed from the quasilinear solutions of the KZK equation. The effects of making these corrections are examined through the simulation of β determination in water. Diffraction corrections are found to have more significant effects than attenuation corrections, and the β values of water can be estimated experimentally with less than 5% errors when the exact second harmonic diffraction corrections are used together with the negligible attenuation correction effects on the basis of linear frequency dependence between attenuation coefficients, α 2 ≃ 2α 1
Jeong, Hyunjo; Zhang, Shuzeng; Barnard, Dan; Li, Xiongbing
2015-09-01
The accurate measurement of acoustic nonlinearity parameter β for fluids or solids generally requires making corrections for diffraction effects due to finite size geometry of transmitter and receiver. These effects are well known in linear acoustics, while those for second harmonic waves have not been well addressed and therefore not properly considered in previous studies. In this work, we explicitly define the attenuation and diffraction corrections using the multi-Gaussian beam (MGB) equations which were developed from the quasilinear solutions of the KZK equation. The effects of making these corrections are examined through the simulation of β determination in water. Diffraction corrections are found to have more significant effects than attenuation corrections, and the β values of water can be estimated experimentally with less than 5% errors when the exact second harmonic diffraction corrections are used together with the negligible attenuation correction effects on the basis of linear frequency dependence between attenuation coefficients, α2 ≃ 2α1.
Vasta, M.; Roberts, J. B.
1998-06-01
Methods for using fourth order spectral quantities to estimate the unknown parameters in non-linear, randomly excited dynamic systems are developed. Attention is focused on the case where only the response is measurable and the excitation is unmeasurable and known only in terms of a stochastic process model. The approach is illustrated through application to a non-linear oscillator with both non-linear damping and stiffness and with excitation modelled as a stationary Gaussian white noise process. The methods have applications in studies of the response of structures to random environmental loads, such as wind and ocean wave forces.
Zeqiri, Bajram; Cook, Ashley; Rétat, Lise; Civale, John; ter Haar, Gail
2015-04-01
The acoustic nonlinearity parameter, B/A, is an important parameter which defines the way a propagating finite amplitude acoustic wave progressively distorts when travelling through any medium. One measurement technique used to determine its value is the finite amplitude insertion substitution (FAIS) method which has been applied to a range of liquid, tissue and tissue-like media. Importantly, in terms of the achievable measurement uncertainties, it is a relative technique. This paper presents a detailed study of the method, employing a number of novel features. The first of these is the use of a large area membrane hydrophone (30 mm aperture) which is used to record the plane-wave component of the acoustic field. This reduces the influence of diffraction on measurements, enabling studies to be carried out within the transducer near-field, with the interrogating transducer, test cell and detector positioned close to one another, an attribute which assists in controlling errors arising from nonlinear distortion in any intervening water path. The second feature is the development of a model which estimates the influence of finite-amplitude distortion as the acoustic wave travels from the rear surface of the test cell to the detector. It is demonstrated that this can lead to a significant systematic error in B/A measurement whose magnitude and direction depends on the acoustic property contrast between the test material and the water-filled equivalent cell. Good qualitative agreement between the model and experiment is reported. B/A measurements are reported undertaken at (20 ± 0.5) °C for two fluids commonly employed as reference materials within the technical literature: Corn Oil and Ethylene Glycol. Samples of an IEC standardised agar-based tissue-mimicking material were also measured. A systematic assessment of measurement uncertainties is presented giving expanded uncertainties in the range ±7% to ±14%, expressed at a confidence level close to 95
A Review of Distributed Parameter Groundwater Management Modeling Methods
Gorelick, Steven M.
1983-04-01
Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.
Choi, Yun Ho; Yoo, Sung Jin
2017-03-28
A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.
Output Feedback Distributed Containment Control for High-Order Nonlinear Multiagent Systems.
Li, Yafeng; Hua, Changchun; Wu, Shuangshuang; Guan, Xinping
2017-01-31
In this paper, we study the problem of output feedback distributed containment control for a class of high-order nonlinear multiagent systems under a fixed undirected graph and a fixed directed graph, respectively. Only the output signals of the systems can be measured. The novel reduced order dynamic gain observer is constructed to estimate the unmeasured state variables of the system with the less conservative condition on nonlinear terms than traditional Lipschitz one. Via the backstepping method, output feedback distributed nonlinear controllers for the followers are designed. By means of the novel first virtual controllers, we separate the estimated state variables of different agents from each other. Consequently, the designed controllers show independence on the estimated state variables of neighbors except outputs information, and the dynamics of each agent can be greatly different, which make the design method have a wider class of applications. Finally, a numerical simulation is presented to illustrate the effectiveness of the proposed method.
PARAMETER ESTIMATION OF THE HYBRID CENSORED LOMAX DISTRIBUTION
Directory of Open Access Journals (Sweden)
Samir Kamel Ashour
2010-12-01
Full Text Available Survival analysis is used in various fields for analyzing data involving the duration between two events. It is also known as event history analysis, lifetime data analysis, reliability analysis or time to event analysis. One of the difficulties which arise in this area is the presence of censored data. The lifetime of an individual is censored when it cannot be exactly measured but partial information is available. Different circumstances can produce different types of censoring. The two most common censoring schemes used in life testing experiments are Type-I and Type-II censoring schemes. Hybrid censoring scheme is mixture of Type-I and Type-II censoring scheme. In this paper we consider the estimation of parameters of Lomax distribution based on hybrid censored data. The parameters are estimated by the maximum likelihood and Bayesian methods. The Fisher information matrix has been obtained and it can be used for constructing asymptotic confidence intervals.
Control of complex dynamics and chaos in distributed parameter systems
Energy Technology Data Exchange (ETDEWEB)
Chakravarti, S.; Marek, M.; Ray, W.H. [Univ. of Wisconsin, Madison, WI (United States)
1995-12-31
This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in the complex quasi-periodic or chaotic spatiotemporal patterns.
Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems
Patan, Maciej
2012-01-01
Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...
Liang, Hua; Miao, Hongyu; Wu, Hulin
2010-03-01
Modeling viral dynamics in HIV/AIDS studies has resulted in deep understanding of pathogenesis of HIV infection from which novel antiviral treatment guidance and strategies have been derived. Viral dynamics models based on nonlinear differential equations have been proposed and well developed over the past few decades. However, it is quite challenging to use experimental or clinical data to estimate the unknown parameters (both constant and time-varying parameters) in complex nonlinear differential equation models. Therefore, investigators usually fix some parameter values, from the literature or by experience, to obtain only parameter estimates of interest from clinical or experimental data. However, when such prior information is not available, it is desirable to determine all the parameter estimates from data. In this paper, we intend to combine the newly developed approaches, a multi-stage smoothing-based (MSSB) method and the spline-enhanced nonlinear least squares (SNLS) approach, to estimate all HIV viral dynamic parameters in a nonlinear differential equation model. In particular, to the best of our knowledge, this is the first attempt to propose a comparatively thorough procedure, accounting for both efficiency and accuracy, to rigorously estimate all key kinetic parameters in a nonlinear differential equation model of HIV dynamics from clinical data. These parameters include the proliferation rate and death rate of uninfected HIV-targeted cells, the average number of virions produced by an infected cell, and the infection rate which is related to the antiviral treatment effect and is time-varying. To validate the estimation methods, we verified the identifiability of the HIV viral dynamic model and performed simulation studies. We applied the proposed techniques to estimate the key HIV viral dynamic parameters for two individual AIDS patients treated with antiretroviral therapies. We demonstrate that HIV viral dynamics can be well characterized and
Su, Fei; Wang, Jiang; Niu, Shuangxia; Li, Huiyan; Deng, Bin; Liu, Chen; Wei, Xile
2018-02-01
The efficacy of deep brain stimulation (DBS) for Parkinson's disease (PD) depends in part on the post-operative programming of stimulation parameters. Closed-loop stimulation is one method to realize the frequent adjustment of stimulation parameters. This paper introduced the nonlinear predictive control method into the online adjustment of DBS amplitude and frequency. This approach was tested in a computational model of basal ganglia-thalamic network. The autoregressive Volterra model was used to identify the process model based on physiological data. Simulation results illustrated the efficiency of closed-loop stimulation methods (amplitude adjustment and frequency adjustment) in improving the relay reliability of thalamic neurons compared with the PD state. Besides, compared with the 130Hz constant DBS the closed-loop stimulation methods can significantly reduce the energy consumption. Through the analysis of inter-spike-intervals (ISIs) distribution of basal ganglia neurons, the evoked network activity by the closed-loop frequency adjustment stimulation was closer to the normal state. Copyright © 2017 Elsevier Ltd. All rights reserved.
Energy Distribution of a Regular Black Hole Solution in Einstein-Nonlinear Electrodynamics
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I. Radinschi
2015-01-01
Full Text Available A study about the energy momentum of a new four-dimensional spherically symmetric, static and charged, regular black hole solution developed in the context of general relativity coupled to nonlinear electrodynamics is presented. Asymptotically, this new black hole solution behaves as the Reissner-Nordström solution only for the particular value μ=4, where μ is a positive integer parameter appearing in the mass function of the solution. The calculations are performed by use of the Einstein, Landau-Lifshitz, Weinberg, and Møller energy momentum complexes. In all the aforementioned prescriptions, the expressions for the energy of the gravitating system considered depend on the mass M of the black hole, its charge q, a positive integer α, and the radial coordinate r. In all these pseudotensorial prescriptions, the momenta are found to vanish, while the Landau-Lifshitz and Weinberg prescriptions give the same result for the energy distribution. In addition, the limiting behavior of the energy for the cases r→∞, r→0, and q=0 is studied. The special case μ=4 and α=3 is also examined. We conclude that the Einstein and Møller energy momentum complexes can be considered as the most reliable tools for the study of the energy momentum localization of a gravitating system.
Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings.
Tang, Yang; Gao, Huijun; Zou, Wei; Kurths, Jürgen
2013-02-01
In this paper, the distributed synchronization problem of networks of agent systems with controllers and nonlinearities subject to Bernoulli switchings is investigated. Controllers and adaptive updating laws injected in each vertex of networks depend on the state information of its neighborhood. Three sets of Bernoulli stochastic variables are introduced to describe the occurrence probabilities of distributed adaptive controllers, updating laws and nonlinearities, respectively. By the Lyapunov functions method, we show that the distributed synchronization of networks composed of agent systems with multiple randomly occurring nonlinearities, multiple randomly occurring controllers, and multiple randomly occurring updating laws can be achieved in mean square under certain criteria. The conditions derived in this paper can be solved by semi-definite programming. Moreover, by mathematical analysis, we find that the coupling strength, the probabilities of the Bernoulli stochastic variables, and the form of nonlinearities have great impacts on the convergence speed and the terminal control strength. The synchronization criteria and the observed phenomena are demonstrated by several numerical simulation examples. In addition, the advantage of distributed adaptive controllers over conventional adaptive controllers is illustrated.
Jeong, Hyunjo; Zhang, Shuzeng; Barnard, Dan; Li, Xiongbing
2016-02-01
Measurements of the acoustic nonlinearity parameter β are frequently made for early detection of damage in various materials. The practical implementation of the measurement technique has been limited to the through-transmission setup for determining the nonlinearity parameter of the second harmonic wave. In this work, a feasibility study is performed to assess the possibility of using pulse-echo methods in determining the nonlinearity parameter β of solids with a stress-free boundary. The multi-Gaussian beam model is developed based on the quasilinear theory of the KZK equation. Simulation results and discussion are presented for the reflected beam fields of the fundamental and second harmonic waves, the uncorrected β behavior and the properties of total correction that incorporate reflection, attenuation and diffraction effects.
Estimating the parameters of a generalized lambda distribution
International Nuclear Information System (INIS)
Fournier, B.; Rupin, N.; Najjar, D.; Iost, A.; Rupin, N.; Bigerelle, M.; Wilcox, R.; Fournier, B.
2007-01-01
The method of moments is a popular technique for estimating the parameters of a generalized lambda distribution (GLD), but published results suggest that the percentile method gives superior results. However, the percentile method cannot be implemented in an automatic fashion, and automatic methods, like the starship method, can lead to prohibitive execution time with large sample sizes. A new estimation method is proposed that is automatic (it does not require the use of special tables or graphs), and it reduces the computational time. Based partly on the usual percentile method, this new method also requires choosing which quantile u to use when fitting a GLD to data. The choice for u is studied and it is found that the best choice depends on the final goal of the modeling process. The sampling distribution of the new estimator is studied and compared to the sampling distribution of estimators that have been proposed. Naturally, all estimators are biased and here it is found that the bias becomes negligible with sample sizes n ≥ 2 * 10(3). The.025 and.975 quantiles of the sampling distribution are investigated, and the difference between these quantiles is found to decrease proportionally to 1/root n.. The same results hold for the moment and percentile estimates. Finally, the influence of the sample size is studied when a normal distribution is modeled by a GLD. Both bounded and unbounded GLDs are used and the bounded GLD turns out to be the most accurate. Indeed it is shown that, up to n = 10(6), bounded GLD modeling cannot be rejected by usual goodness-of-fit tests. (authors)
DEFF Research Database (Denmark)
Hubmer, Simon; Sherina, Ekaterina; Neubauer, Andreas
2018-01-01
. The main result of this paper is the verification of a nonlinearity condition in an infinite dimensional Hilbert space context. This condition guarantees convergence of iterative regularization methods. Furthermore, numerical examples for recovery of the Lam´e parameters from displacement data simulating......We consider a problem of quantitative static elastography, the estimation of the Lam´e parameters from internal displacement field data. This problem is formulated as a nonlinear operator equation. To solve this equation, we investigate the Landweber iteration both analytically and numerically...... a static elastography experiment are presented....
International Nuclear Information System (INIS)
Frolov, A.M.
1986-01-01
Exact variational calculations are treated for few-particle systems in the exponential basis of relative coordinates using nonlinear parameters. The methods of step-by-step optimization and global chaos of nonlinear parameters are applied to calculate the S and P states of ppμ, ddμ, ttμ homonuclear mesomolecules within the error ≤±0.001 eV. The global chaos method turned out to be well applicable to nuclear 3 H and 3 He systems
Energy Technology Data Exchange (ETDEWEB)
Frolov, A M
1986-09-01
Exact variational calculations are treated for few-particle systems in the exponential basis of relative coordinates using nonlinear parameters. The methods of step-by-step optimization and global chaos of nonlinear parameters are applied to calculate the S and P states of pp..mu.., dd..mu.., tt..mu.. homonuclear mesomolecules within the error less than or equal to+-0.001 eV. The global chaos method turned out to be well applicable to nuclear /sup 3/H and /sup 3/He systems.
A Pseudodifferential Approach to Distributed Parameter Systems and Stabilization
DEFF Research Database (Denmark)
Pedersen, Michael
1993-01-01
The recent developments in microlocal analysis and pdeudodifferential boundary calculus are well suited tools in the investigation of a large number of problems occurring in control theory for partial differential equations. We explain some of the basic ideas of a pseudodifferential model....... Differential Equations47 (1983); Appl. Math. Optim.10 (1983)). So far, this work seems to have simplified or unified many of the previous works cited above. We hope that in the future it will even provide stronger and newer results in the boundary control of distributed parameter systems....... (SIAM J. Control Optim.29 (1991)). The pseudo-differential techniques apply easily in the proof of existence of a feedback semigroup for the parabolic and hyperbolic evolution problems, and we reprove in this new setting some of the stabilization results of Lasiecka and Triggiani (see, e.g., J...
DEFF Research Database (Denmark)
Backi, Christoph Josef; Bendtsen, Jan Dimon; Leth, John-Josef
2014-01-01
In this work the stability properties of a nonlinear partial differential equation (PDE) with state–dependent parameters is investigated. Among other things, the PDE describes freezing of foodstuff, and is closely related to the (Potential) Burgers’ Equation. We show that for certain forms of coe...
Energy Technology Data Exchange (ETDEWEB)
Lee, Kyoung Jun; Kim, Jong Beom; Song, Dong Gil; Jhang, Kyung Young [Dept. of Mechanical Engineering, Hanyang University, Seoul (Korea, Republic of)
2015-08-15
In ultrasonic nonlinear parameter measurement using the fast Fourier transform(FFT) of tone-burst signals, the side lobe and leakage on spectrum because of finite time and non-periodicity of signals makes it difficult to measure the harmonic magnitudes accurately. The window function made it possible to resolve this problem. In this study, the effect of the Hanning and Turkey window functions on the experimental measurement of nonlinear parameters was analyzed. In addition, the effect of changes in tone burst signal number with changes in the window function on the experimental measurement was analyzed. The result for both window functions were similar and showed that they enabled reliable nonlinear parameter measurement. However, in order to restore original signal amplitude, the amplitude compensation coefficient should be considered for each window function. On a separate note, the larger number of tone bursts was advantageous for stable nonlinear parameter measurement, but this effect was more advantageous in the case of the Hanning window than the Tukey window.
Energy Technology Data Exchange (ETDEWEB)
Singh, Rishi Pal [Department of Physics, Banaras Hindu University, Varanasi 221005 (India); Singh, Rajendra Kumar, E-mail: rksingh_17@rediffmail.com [Department of Physics, Banaras Hindu University, Varanasi 221005 (India)
2010-11-01
Temperature dependence of acoustic attenuation and non-linearity parameters in lithium hydride and lithium deuteride have been studied for longitudinal and shear modes along various crystallographic directions of propagation in a wide temperature range. Lattice parameter and repulsive parameters have been used as input data and interactions up to next nearest neighbours have been considered to calculate second and third order elastic constants which in turn have been used for evaluating acoustic attenuation and related parameters. The results have been discussed and compared with available data. It is hoped that the present results will serve to stimulate the determination of the acoustic attenuation of these compounds at different temperatures.
Separating the contributions of variability and parameter uncertainty in probability distributions
International Nuclear Information System (INIS)
Sankararaman, S.; Mahadevan, S.
2013-01-01
This paper proposes a computational methodology to quantify the individual contributions of variability and distribution parameter uncertainty to the overall uncertainty in a random variable. Even if the distribution type is assumed to be known, sparse or imprecise data leads to uncertainty about the distribution parameters. If uncertain distribution parameters are represented using probability distributions, then the random variable can be represented using a family of probability distributions. The family of distributions concept has been used to obtain qualitative, graphical inference of the contributions of natural variability and distribution parameter uncertainty. The proposed methodology provides quantitative estimates of the contributions of the two types of uncertainty. Using variance-based global sensitivity analysis, the contributions of variability and distribution parameter uncertainty to the overall uncertainty are computed. The proposed method is developed at two different levels; first, at the level of a variable whose distribution parameters are uncertain, and second, at the level of a model output whose inputs have uncertain distribution parameters
The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression
Directory of Open Access Journals (Sweden)
Chunxiao Zhang
2012-01-01
Full Text Available The prediction of the aero-engine performance parameters is very important for aero-engine condition monitoring and fault diagnosis. In this paper, the chaotic phase space of engine exhaust temperature (EGT time series which come from actual air-borne ACARS data is reconstructed through selecting some suitable nearby points. The partial least square (PLS based on the cubic spline function or the kernel function transformation is adopted to obtain chaotic predictive function of EGT series. The experiment results indicate that the proposed PLS chaotic prediction algorithm based on biweight kernel function transformation has significant advantage in overcoming multicollinearity of the independent variables and solve the stability of regression model. Our predictive NMSE is 16.5 percent less than that of the traditional linear least squares (OLS method and 10.38 percent less than that of the linear PLS approach. At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.
Jeong, Hyunjo; Barnard, Daniel; Cho, Sungjong; Zhang, Shuzeng; Li, Xiongbing
2017-11-01
This paper presents analytical and experimental techniques for accurate determination of the nonlinearity parameter (β) in thick solid samples. When piezoelectric transducers are used for β measurements, the receiver calibration is required to determine the transfer function from which the absolute displacement can be calculated. The measured fundamental and second harmonic displacement amplitudes should be modified to account for beam diffraction and material absorption. All these issues are addressed in this study and the proposed technique is validated through the β measurements of thick solid samples. A simplified self-reciprocity calibration procedure for a broadband receiver is described. The diffraction and attenuation corrections for the fundamental and second harmonics are explicitly derived. Aluminum alloy samples in five different thicknesses (4, 6, 8, 10, 12cm) are prepared and β measurements are made using the finite amplitude, through-transmission method. The effects of diffraction and attenuation corrections on β measurements are systematically investigated. When diffraction and attenuation corrections are all properly made, the variation of β between different thickness samples is found to be less than 3.2%. Copyright © 2017 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Jilani, Asim, E-mail: asim.jilane@gmail.com [Centre of Nanotechnology, King Abdulaziz University, Jeddah (Saudi Arabia); Abdel-wahab, M.Sh [Centre of Nanotechnology, King Abdulaziz University, Jeddah (Saudi Arabia); Materials Science and Nanotechnology Department, Faculty of Postgraduate Studies for Advanced Sciences, Beni -Suef University, Beni-Suef (Egypt); Al-ghamdi, Attieh A. [Centre of Nanotechnology, King Abdulaziz University, Jeddah (Saudi Arabia); Dahlan, Ammar sadik [Department of architecture, faculty of environmental design, King Abdulaziz University, Jeddah (Saudi Arabia); Yahia, I.S. [Department of Physics, Faculty of Science, King Khalid University, P.O. Box 9004, Abha (Saudi Arabia); Nano-Science & Semiconductor Labs, Department of Physics, Faculty of Education, Ain Shams University, Roxy, 11757 Cairo (Egypt)
2016-01-15
The 2.2 wt% of aluminum (Al)-doped zinc oxide (AZO) transparent and preferential c-axis oriented thin films were prepared by using radio frequency (DC/RF) magnetron sputtering at different substrate temperature ranging from room temperature to 200 °C. For structural analysis, X-ray Diffraction (XRD) and Atomic Force Electron Microscope (AFM) was used for morphological studies. The optical parameters such as, optical energy gap, refractive index, extinction coefficient, dielectric loss, tangent loss, first and third order nonlinear optical properties of transparent films were investigated. High transmittance above 90% and highly homogeneous surface were observed in all samples. The substrate temperature plays an important role to get the best transparent conductive oxide thin films. The substrate temperature at 150 °C showed the growth of highly transparent AZO thin film. Energy gap increased with the increased in substrate temperature of Al doped thin films. Dielectric constant and loss were found to be photon energy dependent with substrate temperature. The change in substrate temperature of Al doped thin films also affect the non-liner optical properties of thin films. The value of χ{sup (3)} was found to be changed with the grain size of the thin films that directly affected by the substrate temperature of the pure and Al doped ZnO thin films.
International Nuclear Information System (INIS)
Killough, G.G.; Rope, S.K.; Shleien, B.; Voilleque, P.G.
1999-01-01
A dynamic mass-balance model has been calibrated by a nonlinear parameter estimation method, using time-series measurements of uranium in surface soil near the former Feed Materials Production Center (FMPC) near Fernald, Ohio, USA. The time-series data, taken at six locations near the site boundary since 1971, show a statistically significant downtrend of above-background uranium concentration in surface soil for all six locations. The dynamic model is based on first-order kinetics in a surface-soil compartment 10 cm in depth. Median estimates of weathering rate coefficients for insoluble uranium in this soil compartment range from about 0.065-0.14 year -1 , corresponding to mean transit times of about 7-15 years, depending on the location sampled. The model, calibrated by methods similar to those discussed in this paper, has been used to simulate surface soil kinetics of uranium for a dose reconstruction study. It was also applied, along with other data, to make confirmatory estimates of airborne releases of uranium from the FMPC between 1951 and 1988. Two soil-column models (one diffusive and one advective, the latter similar to a catenary first-order kinetic box model) were calibrated to profile data taken at one of the six locations in 1976. The temporal predictions of the advective model approximate the trend of the time series data for that location. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)
Energy Technology Data Exchange (ETDEWEB)
Jeong, Hyunjo, E-mail: hjjeong@wku.ac.kr [Division of Mechanical and Automotive Engineering, Wonkwang University, Iksan, Jeonbuk 570-749 (Korea, Republic of); Zhang, Shuzeng; Li, Xiongbing [School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan 410075 (China); Barnard, Dan [Center for Nondestructive Evaluation, Iowa State University, Ames, IA 50010 (United States)
2015-09-15
The accurate measurement of acoustic nonlinearity parameter β for fluids or solids generally requires making corrections for diffraction effects due to finite size geometry of transmitter and receiver. These effects are well known in linear acoustics, while those for second harmonic waves have not been well addressed and therefore not properly considered in previous studies. In this work, we explicitly define the attenuation and diffraction corrections using the multi-Gaussian beam (MGB) equations which were developed from the quasilinear solutions of the KZK equation. The effects of making these corrections are examined through the simulation of β determination in water. Diffraction corrections are found to have more significant effects than attenuation corrections, and the β values of water can be estimated experimentally with less than 5% errors when the exact second harmonic diffraction corrections are used together with the negligible attenuation correction effects on the basis of linear frequency dependence between attenuation coefficients, α{sub 2} ≃ 2α{sub 1}.
Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J
2011-09-01
When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.
Nonlinear analysis of field distribution in electric motor with periodicity conditions
Energy Technology Data Exchange (ETDEWEB)
Stabrowski, M M; Sikora, J
1981-01-01
Numerical analysis of electromagnetic field distribution in linear motion tubular electric motor has been performed with the aid of finite element method. Two Fortran programmes for the solution of DBBF and BF large linear symmetric equation systems have been developed for purposes of this analysis. A new iterative algorithm, taking into account iron nonlinearity and periodicity conditions, has been introduced. Final results of the analysis in the form of induction diagrammes and motor driving force are directly useful for motor designers.
International Nuclear Information System (INIS)
Rahimian, M. S.; Sadeghi, S. H. H.; Moini, R.
2003-01-01
Cloud-to-ground lightning strokes can include dangerous overvoltage on power distribution overhead lines. In this paper, a new algorithm is propagated within a distribution network including nonlinear apparatus. The coupling between the lightning channel and the overhead line is based on an antenna theory model and employs the method of moment for solving the governing electric field integral equation. The computed induced overvoltage is then used in the electromagnetic transient program to analyze its propagation within the distribution network. In this regard, the accuracy of the new coupling method is demonstrated by comparing the calculated induced over voltages using the new method and those obtained using the conventional methods. Simulation results are presented to show how the induced overvoltage is penetrated in a typical distribution network, consisting of overhead lines and underground cables, a distribution transformer protected by surge arresters and a three-phase resistive load
Directory of Open Access Journals (Sweden)
Jong-Yun Yoon
2015-08-01
Full Text Available Torsional systems with gear pairs such as the gearbox of wind turbines or vehicle driveline systems inherently show impact phenomena due to clearance-type nonlinearities when the system experiences sinusoidal excitation. This research investigates the vibro-impact energy of unloaded gears in geared systems using the harmonic balance method (HBM in both the frequency and time domains. To achieve accurate simulations, nonlinear models with piecewise and clearance-type nonlinearities and drag torques are defined and implemented in the HBM. Next, the nonlinear frequency responses are examined by focusing on the resonance areas where the impact phenomena occur, along with variations in key parameters such as clutch stiffness, drag torque, and inertias of the flywheel and the unloaded gear. Finally, the effects of the parameters on the vibro-impacts at a specific excitation frequency are explained using bifurcation diagrams. The results are correlated with prior research by defining the gear rattle criteria with key parameters. This article suggests a method to simulate the impact phenomena in torsional systems using the HBM and successfully assesses vibro-impact energy using bifurcation diagrams.
Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang
2017-11-01
The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.
Directory of Open Access Journals (Sweden)
Bin Wang
2016-01-01
Full Text Available This paper studies the application of frequency distributed model for finite time control of a fractional order nonlinear hydroturbine governing system (HGS. Firstly, the mathematical model of HGS with external random disturbances is introduced. Secondly, a novel terminal sliding surface is proposed and its stability to origin is proved based on the frequency distributed model and Lyapunov stability theory. Furthermore, based on finite time stability and sliding mode control theory, a robust control law to ensure the occurrence of the sliding motion in a finite time is designed for stabilization of the fractional order HGS. Finally, simulation results show the effectiveness and robustness of the proposed scheme.
DNN-state identification of 2D distributed parameter systems
Chairez, I.; Fuentes, R.; Poznyak, A.; Poznyak, T.; Escudero, M.; Viana, L.
2012-02-01
There are many examples in science and engineering which are reduced to a set of partial differential equations (PDEs) through a process of mathematical modelling. Nevertheless there exist many sources of uncertainties around the aforementioned mathematical representation. Moreover, to find exact solutions of those PDEs is not a trivial task especially if the PDE is described in two or more dimensions. It is well known that neural networks can approximate a large set of continuous functions defined on a compact set to an arbitrary accuracy. In this article, a strategy based on the differential neural network (DNN) for the non-parametric identification of a mathematical model described by a class of two-dimensional (2D) PDEs is proposed. The adaptive laws for weights ensure the 'practical stability' of the DNN-trajectories to the parabolic 2D-PDE states. To verify the qualitative behaviour of the suggested methodology, here a non-parametric modelling problem for a distributed parameter plant is analysed.
Chu, Dezhang; Lawson, Gareth L; Wiebe, Peter H
2016-05-01
The linear inversion commonly used in fisheries and zooplankton acoustics assumes a constant inversion kernel and ignores the uncertainties associated with the shape and behavior of the scattering targets, as well as other relevant animal parameters. Here, errors of the linear inversion due to uncertainty associated with the inversion kernel are quantified. A scattering model-based nonlinear inversion method is presented that takes into account the nonlinearity of the inverse problem and is able to estimate simultaneously animal abundance and the parameters associated with the scattering model inherent to the kernel. It uses sophisticated scattering models to estimate first, the abundance, and second, the relevant shape and behavioral parameters of the target organisms. Numerical simulations demonstrate that the abundance, size, and behavior (tilt angle) parameters of marine animals (fish or zooplankton) can be accurately inferred from the inversion by using multi-frequency acoustic data. The influence of the singularity and uncertainty in the inversion kernel on the inversion results can be mitigated by examining the singular values for linear inverse problems and employing a non-linear inversion involving a scattering model-based kernel.
Eleiwi, Fadi
2015-07-01
This paper presents a nonlinear Lyapunov-based boundary control for the temperature difference of a membrane distillation boundary layers. The heat transfer mechanisms inside the process are modeled with a 2D advection-diffusion equation. The model is semi-descretized in space, and a nonlinear state-space representation is provided. The control is designed to force the temperature difference along the membrane sides to track a desired reference asymptotically, and hence a desired flux would be generated. Certain constraints are put on the control law inputs to be within an economic range of energy supplies. The effect of the controller gain is discussed. Simulations with real process parameters for the model, and the controller are provided. © 2015 American Automatic Control Council.
Modeling of non-linear CHP efficiency curves in distributed energy systems
DEFF Research Database (Denmark)
Milan, Christian; Stadler, Michael; Cardoso, Gonçalo
2015-01-01
Distributed energy resources gain an increased importance in commercial and industrial building design. Combined heat and power (CHP) units are considered as one of the key technologies for cost and emission reduction in buildings. In order to make optimal decisions on investment and operation...... for these technologies, detailed system models are needed. These models are often formulated as linear programming problems to keep computational costs and complexity in a reasonable range. However, CHP systems involve variations of the efficiency for large nameplate capacity ranges and in case of part load operation......, which can be even of non-linear nature. Since considering these characteristics would turn the models into non-linear problems, in most cases only constant efficiencies are assumed. This paper proposes possible solutions to address this issue. For a mixed integer linear programming problem two...
International Nuclear Information System (INIS)
Heo, Jaeseok; Kim, Kyung Doo
2015-01-01
Highlights: • We developed an interface between an engineering simulation code and statistical analysis software. • Multiple packages of the sensitivity analysis, uncertainty quantification, and parameter estimation algorithms are implemented in the framework. • Parallel computing algorithms are also implemented in the framework to solve multiple computational problems simultaneously. - Abstract: This paper introduces a statistical data analysis toolkit, PAPIRUS, designed to perform the model calibration, uncertainty propagation, Chi-square linearity test, and sensitivity analysis for both linear and nonlinear problems. The PAPIRUS was developed by implementing multiple packages of methodologies, and building an interface between an engineering simulation code and the statistical analysis algorithms. A parallel computing framework is implemented in the PAPIRUS with multiple computing resources and proper communications between the server and the clients of each processor. It was shown that even though a large amount of data is considered for the engineering calculation, the distributions of the model parameters and the calculation results can be quantified accurately with significant reductions in computational effort. A general description about the PAPIRUS with a graphical user interface is presented in Section 2. Sections 2.1–2.5 present the methodologies of data assimilation, uncertainty propagation, Chi-square linearity test, and sensitivity analysis implemented in the toolkit with some results obtained by each module of the software. Parallel computing algorithms adopted in the framework to solve multiple computational problems simultaneously are also summarized in the paper
Energy Technology Data Exchange (ETDEWEB)
Heo, Jaeseok, E-mail: jheo@kaeri.re.kr; Kim, Kyung Doo, E-mail: kdkim@kaeri.re.kr
2015-10-15
Highlights: • We developed an interface between an engineering simulation code and statistical analysis software. • Multiple packages of the sensitivity analysis, uncertainty quantification, and parameter estimation algorithms are implemented in the framework. • Parallel computing algorithms are also implemented in the framework to solve multiple computational problems simultaneously. - Abstract: This paper introduces a statistical data analysis toolkit, PAPIRUS, designed to perform the model calibration, uncertainty propagation, Chi-square linearity test, and sensitivity analysis for both linear and nonlinear problems. The PAPIRUS was developed by implementing multiple packages of methodologies, and building an interface between an engineering simulation code and the statistical analysis algorithms. A parallel computing framework is implemented in the PAPIRUS with multiple computing resources and proper communications between the server and the clients of each processor. It was shown that even though a large amount of data is considered for the engineering calculation, the distributions of the model parameters and the calculation results can be quantified accurately with significant reductions in computational effort. A general description about the PAPIRUS with a graphical user interface is presented in Section 2. Sections 2.1–2.5 present the methodologies of data assimilation, uncertainty propagation, Chi-square linearity test, and sensitivity analysis implemented in the toolkit with some results obtained by each module of the software. Parallel computing algorithms adopted in the framework to solve multiple computational problems simultaneously are also summarized in the paper.
Zorębski, Edward; Zorębski, Michał
2014-01-01
The so-called Beyer nonlinearity parameter B/A is calculated for 1,2- and 1,3-propanediol, 1,2-, 1,3-, and 1,4-butanediol, as well as 2-methyl-2,4-pentanediol by means of a thermodynamic method. The calculations are made for temperatures from (293.15 to 318.15) K and pressures up to 100 MPa. The decrease in B/A values with the increasing pressure is observed. In the case of 1,3-butanediol, the results are compared with corresponding literature data. The consistency is very satisfactory. A simple relationship between the internal pressure and B/A nonlinearity parameter has also been studied. Copyright © 2013 Elsevier B.V. All rights reserved.
van Zyl, J. Martin
2012-01-01
Random variables of the generalized Pareto distribution, can be transformed to that of the Pareto distribution. Explicit expressions exist for the maximum likelihood estimators of the parameters of the Pareto distribution. The performance of the estimation of the shape parameter of generalized Pareto distributed using transformed observations, based on the probability weighted method is tested. It was found to improve the performance of the probability weighted estimator and performs good wit...
A dynamic macromodel for distributed parameter magnetic microactuators
International Nuclear Information System (INIS)
Fang Yuming; Huang Qingan; Li Weihua
2008-01-01
This paper presents a reduced-order model to describe the mechanical behaviour of microbeam-based magnetic devices. The integration for magnetic force is calculated by dividing the microbeam into several segments, and the nonlinear equation set has been developed based on the magnetic circuit principle. In comparison with previous models, the present macromodel accounts for both the micro-magnetic-core reluctance and the coupling between the beam deflection and magnetic force. This macromodel is validated by comparing with the experimental results available in some papers and finite-element solutions
Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.
Shen, Qikun; Shi, Peng; Shi, Yan
2016-12-01
In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.
DEFF Research Database (Denmark)
Chon, K H; Cohen, R J; Holstein-Rathlou, N H
1997-01-01
A linear and nonlinear autoregressive moving average (ARMA) identification algorithm is developed for modeling time series data. The algorithm uses Laguerre expansion of kernals (LEK) to estimate Volterra-Wiener kernals. However, instead of estimating linear and nonlinear system dynamics via moving...... average models, as is the case for the Volterra-Wiener analysis, we propose an ARMA model-based approach. The proposed algorithm is essentially the same as LEK, but this algorithm is extended to include past values of the output as well. Thus, all of the advantages associated with using the Laguerre...
Distributed synchronization of networked drive-response systems: A nonlinear fixed-time protocol.
Zhao, Wen; Liu, Gang; Ma, Xi; He, Bing; Dong, Yunfeng
2017-11-01
The distributed synchronization of networked drive-response systems is investigated in this paper. A novel nonlinear protocol is proposed to ensure that the tracking errors converge to zeros in a fixed-time. By comparison with previous synchronization methods, the present method considers more practical conditions and the synchronization time is not dependent of arbitrary initial conditions but can be offline pre-assign according to the task assignment. Finally, the feasibility and validity of the presented protocol have been illustrated by a numerical simulation. Copyright © 2017. Published by Elsevier Ltd.
International Nuclear Information System (INIS)
Abourabia, A.M.; Hassan, K.M.; Shahein, R.A.
2008-01-01
The formation of (1+1) dimensional ion-acoustic waves (IAWs) in an unmagnetized collisionless plasma consisting of warm ions and isothermal distributed electrons is investigated. The electrodynamics system of equations are solved analytically in terms of a new variable ξκ χ -φ τ, where k=k(ω) is a complex function, at a fixed position. The analytical calculations gives that the critical value σ = τ/τ ∼ 0.25 distinguishes between the linear and nonlinear characters of IAW within the nanosecond time scale. The flow velocity, pressure, number density, electric potential, electric field, mobility and the total energy in the system are estimated and illustrated
Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference.
Venkataraman, Vinay; Turaga, Pavan
2016-12-01
This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification. We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.
Directory of Open Access Journals (Sweden)
S. Vaidyanathan
2013-09-01
Full Text Available This research work describes the modelling of two novel 3-D chaotic systems, the first with a hyperbolic sinusoidal nonlinearity and two quadratic nonlinearities (denoted as system (A and the second with a hyperbolic cosinusoidal nonlinearity and two quadratic nonlinearities (denoted as system (B. In this work, a detailed qualitative analysis of the novel chaotic systems (A and (B has been presented, and the Lyapunov exponents and Kaplan-Yorke dimension of these chaotic systems have been obtained. It is found that the maximal Lyapunov exponent (MLE for the novel chaotic systems (A and (B has a large value, viz. for the system (A and for the system (B. Thus, both the novel chaotic systems (A and (B display strong chaotic behaviour. This research work also discusses the problem of finding adaptive controllers for the global chaos synchronization of identical chaotic systems (A, identical chaotic systems (B and nonidentical chaotic systems (A and (B with unknown system parameters. The adaptive controllers for achieving global chaos synchronization of the novel chaotic systems (A and (B have been derived using adaptive control theory and Lyapunov stability theory. MATLAB simulations have been shown to illustrate the novel chaotic systems (A and (B, and also the adaptive synchronization results derived for the novel chaotic systems (A and (B.
International Nuclear Information System (INIS)
Tajik, M.; Ghasemizad, A.
2008-01-01
In this research, new physical fission reactor parameters which have very sensitive effects on the qualitative behavior of a reactor, are introduced. Therefore, the two, the nonlinear dynamics of two, three and four dimensional, considering almost the effective parameters are formulated for describing nuclear fission reactor systems. Using both analytical and numerical methods, the stability and instability of the given dynamical equations and the conditions of stability are studied in these systems. We have shown that the two parameters of the mean energy residence time in fuel and coolant and also their ratios have the most qualitative effects on the dynamical behaviour of a typical nuclear fission reactor. Increasing or decreasing of these parameters from a captain limit can lead to stability or un stability in a given system
Adaptive distributed parameter and input estimation in linear parabolic PDEs
Mechhoud, Sarra
2016-01-01
First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.
International Nuclear Information System (INIS)
Hamann, Jan; Hannestad, Steen; Melchiorri, Alessandro; Wong, Yvonne Y Y
2008-01-01
We explore and compare the performances of two non-linear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-ΛCDM (CDM: cold dark matter) cosmologies. The first model is the well known Q model, first applied in the analysis of Two-degree Field Galaxy Redshift Survey data. The second, the P model, is inspired by the halo model, in which non-linear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while the two models perform equally well in providing adequate correction for a range of galaxy clustering data in standard ΛCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalization, a technique sometimes used in the marginalization of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended non-linear correction model also because of its physical transparency
Hamann, Jan; Hannestad, Steen; Melchiorri, Alessandro; Wong, Yvonne Y. Y.
2008-07-01
We explore and compare the performances of two non-linear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-ΛCDM (CDM: cold dark matter) cosmologies. The first model is the well known Q model, first applied in the analysis of Two-degree Field Galaxy Redshift Survey data. The second, the P model, is inspired by the halo model, in which non-linear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while the two models perform equally well in providing adequate correction for a range of galaxy clustering data in standard ΛCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalization, a technique sometimes used in the marginalization of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended non-linear correction model also because of its physical transparency.
Eleiwi, Fadi
2016-09-19
This paper presents a nonlinear observer-based Lyapunov control for a membrane distillation (MD) process. The control considers the inlet temperatures of the feed and the permeate solutions as inputs, transforming it to boundary control process, and seeks to maintain the temperature difference along the membrane boundaries around a sufficient level to promote water production. MD process is modeled with advection diffusion equation model in two dimensions, where the diffusion and convection heat transfer mechanisms are best described. Model analysis, effective order reduction and parameters physical interpretation, are provided. Moreover, a nonlinear observer has been designed to provide the control with estimates of the temperature evolution at each time instant. In addition, physical constraints are imposed on the control to have an acceptable range of feasible inputs, and consequently, better energy consumption. Numerical simulations for the complete process with real membrane parameter values are provided, in addition to detailed explanations for the role of the controller and the observer. (C) 2016 Elsevier Ltd. All rights reserved.
Parameter estimation of sub-Gaussian stable distributions
Czech Academy of Sciences Publication Activity Database
Omelchenko, Vadym
2014-01-01
Roč. 50, č. 6 (2014), s. 929-949 ISSN 0023-5954 R&D Projects: GA ČR GA13-14445S Institutional support: RVO:67985556 Keywords : stable distribution * sub-Gaussian distribution * maximum likelihood Subject RIV: AH - Economics Impact factor: 0.541, year: 2014 http://library.utia.cas.cz/separaty/2014/E/omelchenko-0439707.pdf
Simulated Galactic methanol maser distribution to constrain Milky Way parameters
Quiroga-Nuñez, L. H.; van Langevelde, H. J.; Reid, M. J.; Green, J. A.
2017-08-01
Context. Using trigonometric parallaxes and proper motions of masers associated with massive young stars, the Bar and Spiral Structure Legacy (BeSSeL) survey has reported the most accurate values of the Galactic parameters so far. The determination of these parameters with high accuracy has a widespread impact on Galactic and extragalactic measurements. Aims: This research is aimed at establishing the confidence with which such parameters can be determined. This is relevant for the data published in the context of the BeSSeL survey collaboration, but also for future observations, in particular from the southern hemisphere. In addition, some astrophysical properties of the masers can be constrained, notably the luminosity function. Methods: We have simulated the population of maser-bearing young stars associated with Galactic spiral structure, generating several samples and comparing them with the observed samples used in the BeSSeL survey. Consequently, we checked the determination of Galactic parameters for observational biases introduced by the sample selection. Results: Galactic parameters obtained by the BeSSeL survey do not seem to be biased by the sample selection used. In fact, the published error estimates appear to be conservative for most of the parameters. We show that future BeSSeL data and future observations with southern arrays will improve the Galactic parameters estimates and smoothly reduce their mutual correlation. Moreover, by modeling future parallax data with larger distance values and, thus, greater relative uncertainties for a larger numbers of sources, we found that parallax-distance biasing is an important issue. Hence, using fractional parallax uncertainty in the weighting of the motion data is imperative. Finally, the luminosity function for 6.7 GHz methanol masers was determined, allowing us to estimate the number of Galactic methanol masers.
Zhao, Meng; Ding, Baocang
2015-03-01
This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Narayanan, Vignesh; Jagannathan, Sarangapani
2017-06-08
This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.
A Semismooth Newton Method for Nonlinear Parameter Identification Problems with Impulsive Noise
Clason, Christian; Jin, Bangti
2012-01-01
-order condition. The convergence of the solution to the approximating problem as the smoothing parameter goes to zero is shown. A strategy for adaptively selecting the regularization parameter based on a balancing principle is suggested. The efficiency
Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong
2017-11-20
A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.
Energy Technology Data Exchange (ETDEWEB)
Mostaco-Guidolin, Leila B; Ko, Alex C-T; Popescu, Dan P; Smith, Michael S D; Kohlenberg, Elicia K; Sowa, Michael G [Institute for Biodiagnostics, National Research Council Canada, Winnipeg, R3B 1Y6 (Canada); Shiomi, Masashi [Institute of Experimental Animals, School of Medicine, Kobe University, Kobe 650-0017 (Japan); Major, Arkady [Department Electrical and Computer Engineering, University of Manitoba, E3-559 Engineering Building, Winnipeg, R3T 5V6 (Canada)
2011-08-21
The composition and structure of atherosclerotic lesions can be directly related to the risk they pose to the patient. Multimodal nonlinear optical (NLO) microscopy provides a powerful means to visualize the major extracellular components of the plaque that critically determine its structure. Textural features extracted from NLO images were investigated for their utility in providing quantitative descriptors of structural and compositional changes associated with plaque development. Ten texture parameters derived from the image histogram and gray level co-occurrence matrix were examined that highlight specific structural and compositional motifs that distinguish early and late stage plaques. Tonal-texture parameters could be linked to key histological features that characterize vulnerable plaque: the thickness and density of the fibrous cap, size of the atheroma, and the level of inflammation indicated through lipid deposition. Tonal and texture parameters from NLO images provide objective metrics that correspond to structural and biochemical changes that occur within the vessel wall in early and late stage atherosclerosis.
Saputro, D. R. S.; Amalia, F.; Widyaningsih, P.; Affan, R. C.
2018-05-01
Bayesian method is a method that can be used to estimate the parameters of multivariate multiple regression model. Bayesian method has two distributions, there are prior and posterior distributions. Posterior distribution is influenced by the selection of prior distribution. Jeffreys’ prior distribution is a kind of Non-informative prior distribution. This prior is used when the information about parameter not available. Non-informative Jeffreys’ prior distribution is combined with the sample information resulting the posterior distribution. Posterior distribution is used to estimate the parameter. The purposes of this research is to estimate the parameters of multivariate regression model using Bayesian method with Non-informative Jeffreys’ prior distribution. Based on the results and discussion, parameter estimation of β and Σ which were obtained from expected value of random variable of marginal posterior distribution function. The marginal posterior distributions for β and Σ are multivariate normal and inverse Wishart. However, in calculation of the expected value involving integral of a function which difficult to determine the value. Therefore, approach is needed by generating of random samples according to the posterior distribution characteristics of each parameter using Markov chain Monte Carlo (MCMC) Gibbs sampling algorithm.
Distribution Line Parameter Estimation Under Consideration of Measurement Tolerances
DEFF Research Database (Denmark)
Prostejovsky, Alexander; Gehrke, Oliver; Kosek, Anna Magdalena
2016-01-01
conductance that the absolute compensated error is −1.05% and −1.07% for both representations, as opposed to the expected uncompensated error of −79.68%. Identification of a laboratory distribution line using real measurement data grid yields a deviation of 6.75% and 4.00%, respectively, from a calculation...
Ryazanov, V. V.
2007-01-01
By means of an inequality of the information and parametrization of family of distributions of the probabilities, supposing an effective estimation, introduction of the distributions containing time of the first achievement of a level as internal thermodynamic parameter ground.
Charge distributions in transverse coordinate space and in impact parameter space
Energy Technology Data Exchange (ETDEWEB)
Hwang, Dae Sung [Department of Physics, Sejong University, Seoul 143-747 (Korea, Republic of)], E-mail: dshwang@slac.stanford.edu; Kim, Dong Soo [Department of Physics, Kangnung National University, Kangnung 210-702 (Korea, Republic of); Kim, Jonghyun [Department of Physics, Sejong University, Seoul 143-747 (Korea, Republic of)
2008-11-27
We study the charge distributions of the valence quarks inside nucleon in the transverse coordinate space, which is conjugate to the transverse momentum space. We compare the results with the charge distributions in the impact parameter space.
Charge distributions in transverse coordinate space and in impact parameter space
Hwang, Dae Sung; Kim, Dong Soo; Kim, Jonghyun
2008-01-01
We study the charge distributions of the valence quarks inside nucleon in the transverse coordinate space, which is conjugate to the transverse momentum space. We compare the results with the charge distributions in the impact parameter space.
Mathematical Model to estimate the wind power using four-parameter Burr distribution
Liu, Sanming; Wang, Zhijie; Pan, Zhaoxu
2018-03-01
When the real probability of wind speed in the same position needs to be described, the four-parameter Burr distribution is more suitable than other distributions. This paper introduces its important properties and characteristics. Also, the application of the four-parameter Burr distribution in wind speed prediction is discussed, and the expression of probability distribution of output power of wind turbine is deduced.
Improving Distribution Resiliency with Microgrids and State and Parameter Estimation
Energy Technology Data Exchange (ETDEWEB)
Tuffner, Francis K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Tess L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Schneider, Kevin P. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sun, Yannan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Chen-Ching [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Xu, Yin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gourisetti, Sri Nikhil Gup [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2015-09-30
Modern society relies on low-cost reliable electrical power, both to maintain industry, as well as provide basic social services to the populace. When major disturbances occur, such as Hurricane Katrina or Hurricane Sandy, the nation’s electrical infrastructure can experience significant outages. To help prevent the spread of these outages, as well as facilitating faster restoration after an outage, various aspects of improving the resiliency of the power system are needed. Two such approaches are breaking the system into smaller microgrid sections, and to have improved insight into the operations to detect failures or mis-operations before they become critical. Breaking the system into smaller sections of microgrid islands, power can be maintained in smaller areas where distribution generation and energy storage resources are still available, but bulk power generation is no longer connected. Additionally, microgrid systems can maintain service to local pockets of customers when there has been extensive damage to the local distribution system. However, microgrids are grid connected a majority of the time and implementing and operating a microgrid is much different than when islanded. This report discusses work conducted by the Pacific Northwest National Laboratory that developed improvements for simulation tools to capture the characteristics of microgrids and how they can be used to develop new operational strategies. These operational strategies reduce the cost of microgrid operation and increase the reliability and resilience of the nation’s electricity infrastructure. In addition to the ability to break the system into microgrids, improved observability into the state of the distribution grid can make the power system more resilient. State estimation on the transmission system already provides great insight into grid operations and detecting abnormal conditions by leveraging existing measurements. These transmission-level approaches are expanded to using
International Nuclear Information System (INIS)
Plantier, F.; Daridon, J.L.; Lagourette, B.
2002-01-01
Experimental determinations versus pressure of the nonlinear acoustic parameter B/A have been conducted for methanol, 1-butanol and 1-octanol in the pressure range 0-50 MPa and temperature range 303.15-373.15 K. These measurements proceed from an experimental technique based on a phase comparison method allowing to measure the change in sound speed with the pressure for an isentropic process. The value of B/A is found to decrease with increasing pressure and seems to be an increasing function of temperature. A comparison with the data determined numerically by the classical thermodynamic method has also been performed. (author)
CSIR Research Space (South Africa)
Salmon, BP
2017-09-01
Full Text Available be de- rived for Equation (8) as shown in [27]. The Poincare´- Bendixson theorem states that a differential equation with a three-dimensional phase plane can be chaotic [28]. Hence Equation (8) is a nonlinear deterministic system that can exert... model parameters. Lemma 1. The characteristics of a differential equation can be investigated with the aid of a phase plane plot, which illustrates the limit cycles of the solutions. A three-dimensional phase plane representation that is autonomous can...
International Nuclear Information System (INIS)
Miller, G.; Martz, H.; Bertelli, L.; Melo, D.
2008-01-01
A simplified biokinetic model for 137 Cs has six parameters representing transfer of material to and from various compartments. Using a Bayesian analysis, the joint probability distribution of these six parameters is determined empirically for two cases with quite a lot of bioassay data. The distribution is found to be a multivariate log-normal. Correlations between different parameters are obtained. The method utilises a fairly large number of pre-determined forward biokinetic calculations, whose results are stored in interpolation tables. Four different methods to sample the multidimensional parameter space with a limited number of samples are investigated: random, stratified, Latin Hypercube sampling with a uniform distribution of parameters and importance sampling using a lognormal distribution that approximates the posterior distribution. The importance sampling method gives much smaller sampling uncertainty. No sampling method-dependent differences are perceptible for the uniform distribution methods. (authors)
Modeling exposure–lag–response associations with distributed lag non-linear models
Gasparrini, Antonio
2014-01-01
In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure–lag–response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24027094
Directory of Open Access Journals (Sweden)
Guoguang Wen
2014-01-01
Full Text Available This paper mainly addresses the distributed consensus tracking problem for second-order nonlinear multiagent systems with a specified reference trajectory. The dynamics of each follower consists of two terms: nonlinear inherent dynamics and a simple communication protocol relying only on the position and velocity information of its neighbors. The consensus reference is taken as a virtual leader, whose output is only its position and velocity information that is available to only a subset of a group of followers. To achieve consensus tracking, a class of nonsmooth control protocols is proposed which reply on the relative information among the neighboring agents. Then some corresponding sufficient conditions are derived. It is shown that if the communication graph associated with the virtual leader and followers is connected at each time instant, the consensus can be achieved at least globally exponentially with the proposed protocol. Rigorous proofs are given by using graph theory, matrix theory, and Lyapunov theory. Finally, numerical examples are presented to illustrate the theoretical analysis.
Nonlinear electron-density distribution around point defects in simple metals. I. Formulation
International Nuclear Information System (INIS)
Gupta, A.K.; Jena, P.; Singwi, K.S.
1978-01-01
Modification, which is exact in the limit of long wavelength, of the nonlinear theory of Sjoelander and Stott of electron distribution around point defects is given. This modification consists in writing a nonlinear integral equations for the Fourier transform γ 12 (q) of the induced charge density surrounding the point defect, which includes a term involving the density derivative of γ 12 (q). A generalization of the Pauli-Feynman coupling-constant-integration method, together with the Kohn-Sham formalism, is used to exactly determine the coefficient of this derivative term in the long-wavelength limit. The theory is then used to calculate electron-density profiles around a vacancy, an eight-atom void, and a point ion. The results are compared with those of (i) a linear theory, (ii) Sjoelander-Stott theory, and (iii) a fully self-consistent calculation based on the density-functional formalism of Kohn and Sham. It is found that in the case of a vacancy, the results of the present theory are in very good agreement with those based on Kohn-Sham formalism, whereas in the case of a singular attractive potential of a proton, the results are quite poor in the vicinity of the proton, but much better for larger distances. A critical discussion of the theory vis a vis the Kohn-Sham formalism is also given. Some applications of the theory are pointed out
Directory of Open Access Journals (Sweden)
Jie Peng
Full Text Available The vacuum preloading is an effective method which is widely used in ground treatment. In consolidation analysis, the soil around prefabricated vertical drain (PVD is traditionally divided into smear zone and undisturbed zone, both with constant permeability. In reality, the permeability of soil changes continuously within the smear zone. In this study, the horizontal permeability coefficient of soil within the smear zone is described by an exponential function of radial distance. A solution for vacuum preloading consolidation considers the nonlinear distribution of horizontal permeability within the smear zone is presented and compared with previous analytical results as well as a numerical solution, the results show that the presented solution correlates well with the numerical solution, and is more precise than previous analytical solution.
da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G
2016-07-08
Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.
International Nuclear Information System (INIS)
Prakash, Deo; Shaaban, E.R.; Shapaan, M.; Mohamed, S.H.; Othman, A.A.; Verma, K.D.
2016-01-01
Highlights: • Combined experimental and theoretical researches on ZnSe Thin Films. • The film thickness and refractive index were determined using envelope method. • The absorption coefficient and the energy gap were calculated. • Dispersion parameters were determined using Wemple-DiDomenico relation. • The third order susceptibility and nonlinear refractive index were calculated. - Abstract: Zinc selenide (ZnSe) thin films with different thicknesses were evaporated onto glass substrates using the thermal evaporation technique. X-ray diffraction analysis confirmed that both the film and powder have cubic zinc-blende structure. The fundamental optical parameters like absorption coefficient, extinction coefficient and band gap were evaluated in transparent region of transmittance and reflectance spectrum. The optical transition of the films was found to be allowed, where the energy gap increased from 2.576 to 2.702 eV with increasing film thickness. Also, the refractive index value increase with increasing film thickness. The refractive indices evaluated through envelope method were extrapolated by Cauchy dispersion relationship over the whole spectra range. Additionally, the dispersion of refractive index was determined in terms of Wemple-DiDomenico single oscillator model. Third order susceptibility and nonlinear refractive index were determined for different thickness of ZnSe thin films.
Energy Technology Data Exchange (ETDEWEB)
Prakash, Deo [School of Computer Science & Engineering, Faculty of Engineering, SMVD University, Kakryal, Katra 182320, J& K (India); Shaaban, E.R., E-mail: esam_ramadan2008@yahoo.com [Physics Department, Faculty of Science, Al-Azhar University, Assiut 71542 (Egypt); Shapaan, M. [Department of Physics, Faculty of Science, Al-Azahar University, Cairo (Egypt); Mohamed, S.H. [Physics Department, Faculty of Science, Sohag University, 82524 Sohag (Egypt); Othman, A.A. [Physics Department, Faculty of Science, Assiut University, Assiut 71516 (Egypt); Verma, K.D., E-mail: kdverma1215868@gmail.com [Material Science Research Laboratory, Department of Physics, S. V. College, Aligarh 202001, U.P. (India)
2016-08-15
Highlights: • Combined experimental and theoretical researches on ZnSe Thin Films. • The film thickness and refractive index were determined using envelope method. • The absorption coefficient and the energy gap were calculated. • Dispersion parameters were determined using Wemple-DiDomenico relation. • The third order susceptibility and nonlinear refractive index were calculated. - Abstract: Zinc selenide (ZnSe) thin films with different thicknesses were evaporated onto glass substrates using the thermal evaporation technique. X-ray diffraction analysis confirmed that both the film and powder have cubic zinc-blende structure. The fundamental optical parameters like absorption coefficient, extinction coefficient and band gap were evaluated in transparent region of transmittance and reflectance spectrum. The optical transition of the films was found to be allowed, where the energy gap increased from 2.576 to 2.702 eV with increasing film thickness. Also, the refractive index value increase with increasing film thickness. The refractive indices evaluated through envelope method were extrapolated by Cauchy dispersion relationship over the whole spectra range. Additionally, the dispersion of refractive index was determined in terms of Wemple-DiDomenico single oscillator model. Third order susceptibility and nonlinear refractive index were determined for different thickness of ZnSe thin films.
Directory of Open Access Journals (Sweden)
Peiguang Wang
2014-01-01
Full Text Available This paper establishes variation of parameters formula for impulsive differential equations with initial time difference. As an application, one of the results is used to investigate stability properties of solutions.
Nonlinear saturation of wave packets excited by low-energy electron horseshoe distributions.
Krafft, C; Volokitin, A
2013-05-01
Horseshoe distributions are shell-like particle distributions that can arise in space and laboratory plasmas when particle beams propagate into increasing magnetic fields. The present paper studies the stability and the dynamics of wave packets interacting resonantly with electrons presenting low-energy horseshoe or shell-type velocity distributions in a magnetized plasma. The linear instability growth rates are determined as a function of the ratio of the plasma to the cyclotron frequencies, of the velocity and the opening angle of the horseshoe, and of the relative thickness of the shell. The nonlinear stage of the instability is investigated numerically using a symplectic code based on a three-dimensional Hamiltonian model. Simulation results show that the dynamics of the system is mainly governed by wave-particle interactions at Landau and normal cyclotron resonances and that the high-order normal cyclotron resonances play an essential role. Specific features of the dynamics of particles interacting simultaneously with two or more waves at resonances of different natures and orders are discussed, showing that such complex processes determine the main characteristics of the wave spectrum's evolution. Simulations with wave packets presenting quasicontinuous spectra provide a full picture of the relaxation of the horseshoe distribution, revealing two main phases of the evolution: an initial stage of wave energy growth, characterized by a fast filling of the shell, and a second phase of slow damping of the wave energy, accompanied by final adjustments of the electron distribution. The influence of the density inhomogeneity along the horseshoe on the wave-particle dynamics is also discussed.
Nonlinear parameter estimation in inviscid compressible flows in presence of uncertainties
International Nuclear Information System (INIS)
Jemcov, A.; Mathur, S.
2004-01-01
The focus of this paper is on the formulation and solution of inverse problems of parameter estimation using algorithmic differentiation. The inverse problem formulated here seeks to determine the input parameters that minimize a least squares functional with respect to certain target data. The formulation allows for uncertainty in the target data by considering the least squares functional in a stochastic basis described by the covariance of the target data. Furthermore, to allow for robust design, the formulation also accounts for uncertainties in the input parameters. This is achieved using the method of propagation of uncertainties using the directional derivatives of the output parameters with respect to unknown parameters. The required derivatives are calculated simultaneously with the solution using generic programming exploiting the template and operator overloading features of the C++ language. The methodology described here is general and applicable to any numerical solution procedure for any set of governing equations but for the purpose of this paper we consider a finite volume solution of the compressible Euler equations. In particular, we illustrate the method for the case of supersonic flow in a duct with a wedge. The parameter to be determined is the inlet Mach number and the target data is the axial component of velocity at the exit of the duct. (author)
Energy Technology Data Exchange (ETDEWEB)
Kim, Sooyoung; Yoon, Suk-Jin, E-mail: sjyoon0691@yonsei.ac.kr [Department of Astronomy and Center for Galaxy Evolution Research, Yonsei University, Seoul 120-749 (Korea, Republic of)
2017-07-01
Spectroscopy on the globular cluster (GC) system of NGC 5128 revealed bimodality in absorption-line index distributions of its old GCs. GC division is a widely observed and studied phenomenon whose interpretation has depicted host galaxy formation and evolution such that it harbors two distinct metallicity groups. Such a conventional view of GC bimodality has mainly been based on photometry. The recent GC photometric data, however, presented an alternative perspective in which the nonlinear metallicity-to-color transformation is responsible for color bimodality of GC systems. Here we apply the same line of analysis to the spectral indices and examine the absorption-line index versus metallicity relations for the NGC 5128 GC system. NGC 5128 GCs display nonlinearity in the metallicity-index planes, most prominently for the Balmer lines and by a non-negligible degree for the metallicity-sensitive magnesium line. We demonstrate that the observed spectroscopic division of NGC 5128 GCs can be caused by the nonlinear nature of the metallicity-to-index conversions and thus one does not need to resort to two separate GC subgroups. Our analysis incorporating this nonlinearity provides a new perspective on the structure of NGC 5128's GC system, and a further piece to the global picture of the formation of GC systems and their host galaxies.
A distributed parameter wire model for transient electrical discharges
International Nuclear Information System (INIS)
Maier, W.B. II; Kadish, A.; Sutherland, C.D.; Robiscoe, R.T.
1990-01-01
A model for freely propagating transient electrical discharges, such as lightning and punch-through arcs, is developed in this paper. We describe the electromagnetic fields by Maxwell's equations and we represent the interaction of electric fields with the medium to produce current by ∂J/∂t=ω 2 (E-E*J)/4π, where ω and E* are parameters characteristic of the medium, J≡current density, and J≡J/|J|. We illustrate the properties of this model for small-diameter, guided, cylindrically symmetric discharges. Analytic, numerical, and approximate solutions are given for special cases. The model describes, in a new and comprehensive fashion, certain macroscopic discharge properties, such as threshold behavior, quenching and reignition, path tortuosity, discharge termination with nonzero charge density remaining along the discharge path, and other experimentally observed discharge phenomena. Fields, current densities, and charge densities are quantitatively determined from given boundary and initial conditions. We suggest that many macroscopic discharge properties are properly explained by the model as electromagnetic phenomena, and we discuss extensions of the model to include chemistry, principally ionization and recombination
Khanmohammadi, Neda; Rezaie, Hossein; Montaseri, Majid; Behmanesh, Javad
2017-10-01
The reference evapotranspiration (ET0) plays an important role in water management plans in arid or semi-arid countries such as Iran. For this reason, the regional analysis of this parameter is important. But, ET0 process is affected by several meteorological parameters such as wind speed, solar radiation, temperature and relative humidity. Therefore, the effect of distribution type of effective meteorological variables on ET0 distribution was analyzed. For this purpose, the regional probability distribution of the annual ET0 and its effective parameters were selected. Used data in this research was recorded data at 30 synoptic stations of Iran during 1960-2014. Using the probability plot correlation coefficient (PPCC) test and the L-moment method, five common distributions were compared and the best distribution was selected. The results of PPCC test and L-moment diagram indicated that the Pearson type III distribution was the best probability distribution for fitting annual ET0 and its four effective parameters. The results of RMSE showed that the ability of the PPCC test and L-moment method for regional analysis of reference evapotranspiration and its effective parameters was similar. The results also showed that the distribution type of the parameters which affected ET0 values can affect the distribution of reference evapotranspiration.
Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu
2015-09-01
In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.
Directory of Open Access Journals (Sweden)
Yacouba Simporé
2016-01-01
Full Text Available We first prove a null controllability result for a nonlinear system derived from a nonlinear population dynamics model. In order to tackle the controllability problem we use an adapted Carleman inequality. Next we consider the nonlinear population dynamics model with a source term called the pollution term. In order to obtain information on the pollution term we use the method of sentinel.
Parameter estimation of the zero inflated negative binomial beta exponential distribution
Sirichantra, Chutima; Bodhisuwan, Winai
2017-11-01
The zero inflated negative binomial-beta exponential (ZINB-BE) distribution is developed, it is an alternative distribution for the excessive zero counts with overdispersion. The ZINB-BE distribution is a mixture of two distributions which are Bernoulli and negative binomial-beta exponential distributions. In this work, some characteristics of the proposed distribution are presented, such as, mean and variance. The maximum likelihood estimation is applied to parameter estimation of the proposed distribution. Finally some results of Monte Carlo simulation study, it seems to have high-efficiency when the sample size is large.
Fang, Fang; Ni, Bing-Jie; Yu, Han-Qing
2009-06-01
In this study, weighted non-linear least-squares analysis and accelerating genetic algorithm are integrated to estimate the kinetic parameters of substrate consumption and storage product formation of activated sludge. A storage product formation equation is developed and used to construct the objective function for the determination of its production kinetics. The weighted least-squares analysis is employed to calculate the differences in the storage product concentration between the model predictions and the experimental data as the sum of squared weighted errors. The kinetic parameters for the substrate consumption and the storage product formation are estimated to be the maximum heterotrophic growth rate of 0.121/h, the yield coefficient of 0.44 mg CODX/mg CODS (COD, chemical oxygen demand) and the substrate half saturation constant of 16.9 mg/L, respectively, by minimizing the objective function using a real-coding-based accelerating genetic algorithm. Also, the fraction of substrate electrons diverted to the storage product formation is estimated to be 0.43 mg CODSTO/mg CODS. The validity of our approach is confirmed by the results of independent tests and the kinetic parameter values reported in literature, suggesting that this approach could be useful to evaluate the product formation kinetics of mixed cultures like activated sludge. More importantly, as this integrated approach could estimate the kinetic parameters rapidly and accurately, it could be applied to other biological processes.
Non-linearity parameter of binary liquid mixtures at elevated pressures
Indian Academy of Sciences (India)
parameter B/A of four binary liquid mixtures using Tong and Dong equation at high pressures and .... in general as regular or ideal as no recognized association takes place between the unlike molecules. In this case ... Using the definition and.
DEFF Research Database (Denmark)
Sommer, Helle Mølgaard; Holst, Helle; Spliid, Henrik
1995-01-01
Three identical microbiological experiments were carried out and analysed in order to examine the variability of the parameter estimates. The microbiological system consisted of a substrate (toluene) and a biomass (pure culture) mixed together in an aquifer medium. The degradation of the substrate...
Linear and Nonlinear Time-Frequency Analysis for Parameter Estimation of Resident Space Objects
2017-02-22
Vector Machines”, IEEE Trans. on Neural Networks , vol. 13(2), March 2002. [11] T. M. Mitchell, “Machine Learning”, McGraw-Hill, 1997 76DISTRIBUTION A...by the observer is given by: L = n∑ j=1 S(µ, µ0, α)ρjaj (31) where S is the scattering law (or Bidirectional Reflectance Distribution Function, BRDF...vector ma- chine learning”, Adv. Neural Information Processing Systems (NIPS*2000), Cambridge, MA, MIT Press, vol.13, 2001. [9] J., Wetson, and C
Kartono; Suryadi, D.; Herman, T.
2018-01-01
This study aimed to analyze the enhancement of non-linear learning (NLL) in the online tutorial (OT) content to students’ knowledge of normal distribution application (KONDA). KONDA is a competence expected to be achieved after students studied the topic of normal distribution application in the course named Education Statistics. The analysis was performed by quasi-experiment study design. The subject of the study was divided into an experimental class that was given OT content in NLL model and a control class which was given OT content in conventional learning (CL) model. Data used in this study were the results of online objective tests to measure students’ statistical prior knowledge (SPK) and students’ pre- and post-test of KONDA. The statistical analysis test of a gain score of KONDA of students who had low and moderate SPK’s scores showed students’ KONDA who learn OT content with NLL model was better than students’ KONDA who learn OT content with CL model. Meanwhile, for students who had high SPK’s scores, the gain score of students who learn OT content with NLL model had relatively similar with the gain score of students who learn OT content with CL model. Based on those findings it could be concluded that the NLL model applied to OT content could enhance KONDA of students in low and moderate SPK’s levels. Extra and more challenging didactical situation was needed for students in high SPK’s level to achieve the significant gain score.
Minimising the Kullback–Leibler Divergence for Model Selection in Distributed Nonlinear Systems
Directory of Open Access Journals (Sweden)
Oliver M. Cliff
2018-01-01
Full Text Available The Kullback–Leibler (KL divergence is a fundamental measure of information geometry that is used in a variety of contexts in artificial intelligence. We show that, when system dynamics are given by distributed nonlinear systems, this measure can be decomposed as a function of two information-theoretic measures, transfer entropy and stochastic interaction. More specifically, these measures are applicable when selecting a candidate model for a distributed system, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic graph (DAG that characterises the unidirectional coupling between subsystems. Standard approaches to structure learning are not applicable in this framework due to the hidden variables; however, we can exploit the properties of certain dynamical systems to formulate exact methods based on differential topology. We approach the problem by using reconstruction theorems to derive an analytical expression for the KL divergence of a candidate DAG from the observed dataset. Using this result, we present a scoring function based on transfer entropy to be used as a subroutine in a structure learning algorithm. We then demonstrate its use in recovering the structure of coupled Lorenz and Rössler systems.
Errors in determination of irregularity factor for distributed parameters in a reactor core
International Nuclear Information System (INIS)
Vlasov, V.A.; Zajtsev, M.P.; Il'ina, L.I.; Postnikov, V.V.
1988-01-01
Two types errors (measurement error and error of regulation of reactor core distributed parameters), offen met during high-power density reactor operation, are analyzed. Consideration is given to errors in determination of irregularity factor for radial power distribution for a hot channel under conditions of its minimization and for the conditions when the regulation of relative power distribution is absent. The first regime is investigated by the method of statistic experiment using the program of neutron-physical calculation optimization taking as an example a large channel water cooled graphite moderated reactor. It is concluded that it is necessary, to take into account the complex interaction of measurement error with the error of parameter profiling over the core both for conditions of continuous manual or automatic parameter regulation (optimization) and for the conditions without regulation namely at a priore equalized distribution. When evaluating the error of distributed parameter control
Ren, Yefei; Wen, Ruizhi; Yao, Xinxin; Ji, Kun
2017-08-01
The consideration of soil nonlinearity is important for the accurate estimation of the site response. To evaluate the soil nonlinearity during the 2008 Ms8.0 Wenchuan Earthquake, 33 strong-motion records obtained from the main shock and 890 records from 157 aftershocks were collected for this study. The horizontal-to-vertical spectral ratio (HVSR) method was used to calculate five parameters: the ratio of predominant frequency (RFp), degree of nonlinearity (DNL), absolute degree of nonlinearity (ADNL), frequency of nonlinearity (fNL), and percentage of nonlinearity (PNL). The purpose of this study was to evaluate the soil nonlinearity level of 33 strong-motion stations and to investigate the characteristics, performance, and effective usage of these five parameters. Their correlations with the peak ground acceleration (PGA), peak ground velocity (PGV), average uppermost 30-m shear-wave velocity ( V S30), and maximum amplitude of HVSR ( A max) were investigated. The results showed that all five parameters correlate well with PGA and PGV. The DNL, ADNL, and PNL also show a good correlation with A max, which means that the degree of soil nonlinearity not only depends on the ground-motion amplitude (e.g., PGA and PGV) but also on the site condition. The fNL correlates with PGA and PGV but shows no correlation with either A max or V S30, implying that the frequency width affected by the soil nonlinearity predominantly depends on the ground-motion amplitude rather than the site condition. At 16 of the 33 stations analyzed in this study, the site response showed evident (i.e., strong and medium) nonlinearity during the main shock of the Wenchuan Earthquake, where the ground-motion level was almost beyond the threshold of PGA > 200 cm/s2 or PGV > 15 cm/s. The site response showed weak and no nonlinearity at the other 14 and 3 stations. These results also confirm that RFp, DNL, ADNL, and PNL are effective in identifying the soil nonlinearity behavior. The identification
Directory of Open Access Journals (Sweden)
Jian Liu
Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Liu, Jian; Liu, Kexin; Liu, Shutang
2017-01-01
In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Neubert, M.; Winkler, J.
2012-12-01
This contribution continues an article series [1,2] about the nonlinear model-based control of the Czochralski crystal growth process. The key idea of the presented approach is to use a sophisticated combination of nonlinear model-based and conventional (linear) PI controllers for tracking of both, crystal radius and growth rate. Using heater power and pulling speed as manipulated variables several controller structures are possible. The present part tries to systematize the properties of the materials to be grown in order to get unambiguous decision criteria for a most profitable choice of the controller structure. For this purpose a material specific constant M called interface mobility and a more process specific constant S called system response number are introduced. While the first one summarizes important material properties like thermal conductivity and latent heat the latter one characterizes the process by evaluating the average axial thermal gradients at the phase boundary and the actual growth rate at which the crystal is grown. Furthermore these characteristic numbers are useful for establishing a scheduling strategy for the PI controller parameters in order to improve the controller performance. Finally, both numbers give a better understanding of the general thermal system dynamics of the Czochralski technique.
Lam, H K; Leung, Frank H F
2005-04-01
This paper presents a fuzzy controller, which involves a fuzzy combination of local fuzzy and global switching state-feedback controllers, for nonlinear systems subject to parameter uncertainties with known bounds. The nonlinear system is represented by a fuzzy combined Takagi-Sugeno-Kang model, which is a fuzzy combination of the global and local fuzzy plant models. By combining the local fuzzy and global switching state-feedback controllers using fuzzy logic techniques, the advantages of both controllers can be retained and the undesirable chattering effect introduced by the global switching state-feedback controller can be eliminated. The steady-state error introduced by the global switching state-feedback controller when a saturation function is used can also be removed. Stability conditions, which are related to the system matrices of the local and global closed-loop systems, are derived to guarantee the closed-loop system stability. An application example will be given to demonstrate the merits of the proposed approach.
Directory of Open Access Journals (Sweden)
Youliang Fu
2016-01-01
Full Text Available This paper is concerned with the asymptotic properties of solutions to a third-order nonlinear neutral delay differential equation with distributed deviating arguments. Several new theorems are obtained which ensure that every solution to this equation either is oscillatory or tends to zero. Two illustrative examples are included.
Huang, Dan; Chen, Xuejuan; Gong, Qi; Yuan, Chaoqun; Ding, Hui; Bai, Jing; Zhu, Hui; Fu, Zhujun; Yu, Rongbin; Liu, Hu
2016-01-01
This survey was conducted to determine the testability, distribution and associations of ocular biometric parameters in Chinese preschool children. Ocular biometric examinations, including the axial length (AL) and corneal radius of curvature (CR), were conducted on 1,688 3-year-old subjects by using an IOLMaster in August 2015. Anthropometric parameters, including height and weight, were measured according to a standardized protocol, and body mass index (BMI) was calculated. The testability was 93.7% for the AL and 78.6% for the CR overall, and both measures improved with age. Girls performed slightly better in AL measurements (P = 0.08), and the difference in CR was statistically significant (P < 0.05). The AL distribution was normal in girls (P = 0.12), whereas it was not in boys (P < 0.05). For CR1, all subgroups presented normal distributions (P = 0.16 for boys; P = 0.20 for girls), but the distribution varied when the subgroups were combined (P < 0.05). CR2 presented a normal distribution (P = 0.11), whereas the AL/CR ratio was abnormal (P < 0.001). Boys exhibited a significantly longer AL, a greater CR and a greater AL/CR ratio than girls (all P < 0.001). PMID:27384307
A nonlinear model for frequency dispersion and DC intrinsic parameter extraction for GaN-based HEMT
Nguyen, Tung The-Lam; Kim, Sam-Dong
2017-11-01
We propose in this study a practical nonlinear model for the AlGaN/GaN high electron mobility transistors (HEMTs) to extract DC intrinsic transconductance (gmDC), output conductance (gdsDC), and electron mobility from the intrinsic parameter set measured at high frequencies. An excellent agreement in I-V characteristics of the model with a fitting error of 0.11% enables us successfully extract the gmDC, gdsDC, and the total transconductance dispersion. For this model, we also present a reliable analysis scheme wherein the frequency dispersion effect due regional surface states in AlGaN/GaN HEMTs is taken into account under various bias conditions.
Lambert, Ronald J W; Mytilinaios, Ioannis; Maitland, Luke; Brown, Angus M
2012-08-01
This study describes a method to obtain parameter confidence intervals from the fitting of non-linear functions to experimental data, using the SOLVER and Analysis ToolPaK Add-In of the Microsoft Excel spreadsheet. Previously we have shown that Excel can fit complex multiple functions to biological data, obtaining values equivalent to those returned by more specialized statistical or mathematical software. However, a disadvantage of using the Excel method was the inability to return confidence intervals for the computed parameters or the correlations between them. Using a simple Monte-Carlo procedure within the Excel spreadsheet (without recourse to programming), SOLVER can provide parameter estimates (up to 200 at a time) for multiple 'virtual' data sets, from which the required confidence intervals and correlation coefficients can be obtained. The general utility of the method is exemplified by applying it to the analysis of the growth of Listeria monocytogenes, the growth inhibition of Pseudomonas aeruginosa by chlorhexidine and the further analysis of the electrophysiological data from the compound action potential of the rodent optic nerve. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Miró, Anton; Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Egea, Jose A; Jiménez, Laureano
2012-05-10
The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.
Digital Repository Service at National Institute of Oceanography (India)
Sarma, V.V.; Rao, T.V.N.; RamaRaju, V.S.; Rathod, V.; Suguna, C.
The distribution of hydrochemical parameters in the coastal waters off Visakhapatnam during the July 1979-June 1980 showed distinct changes with time The observed supersaturation and saturation of oxygen in surface waters was due to favourable...
Distributed Optimal Consensus Control for Nonlinear Multiagent System With Unknown Dynamic.
Zhang, Jilie; Zhang, Huaguang; Feng, Tao
2017-08-01
This paper focuses on the distributed optimal cooperative control for continuous-time nonlinear multiagent systems (MASs) with completely unknown dynamics via adaptive dynamic programming (ADP) technology. By introducing predesigned extra compensators, the augmented neighborhood error systems are derived, which successfully circumvents the system knowledge requirement for ADP. It is revealed that the optimal consensus protocols actually work as the solutions of the MAS differential game. Policy iteration algorithm is adopted, and it is theoretically proved that the iterative value function sequence strictly converges to the solution of the coupled Hamilton-Jacobi-Bellman equation. Based on this point, a novel online iterative scheme is proposed, which runs based on the data sampled from the augmented system and the gradient of the value function. Neural networks are employed to implement the algorithm and the weights are updated, in the least-square sense, to the ideal value, which yields approximated optimal consensus protocols. Finally, a numerical example is given to illustrate the effectiveness of the proposed scheme.
Narayanan, Vignesh; Jagannathan, Sarangapani
2017-09-07
In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.
Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan
2016-01-01
This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability.
Directory of Open Access Journals (Sweden)
Yoon Soo ePark
2016-02-01
Full Text Available This study investigates the impact of item parameter drift (IPD on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effect on item parameters and examinee ability.
From conservation laws to port-Hamiltonian representations of distributed-parameter systems
Maschke, B.M.; van der Schaft, Arjan; Piztek, P.
Abstract: In this paper it is shown how the port-Hamiltonian formulation of distributed-parameter systems is closely related to the general thermodynamic framework of systems of conservation laws and closure equations. The situation turns out to be similar to the lumped-parameter case where the
Shivakumar, J.; Ashok, M. H.; Khadakbhavi, Vishwanath; Pujari, Sanjay; Nandurkar, Santosh
2018-02-01
The present work focuses on geometrically nonlinear transient analysis of laminated smart composite plates integrated with the patches of Active fiber composites (AFC) using Active constrained layer damping (ACLD) as the distributed actuators. The analysis has been carried out using generalised energy based finite element model. The coupled electromechanical finite element model is derived using Von Karman type nonlinear strain displacement relations and a first-order shear deformation theory (FSDT). Eight-node iso-parametric serendipity elements are used for discretization of the overall plate integrated with AFC patch material. The viscoelastic constrained layer is modelled using GHM method. The numerical results shows the improvement in the active damping characteristics of the laminated composite plates over the passive damping for suppressing the geometrically nonlinear transient vibrations of laminated composite plates with AFC as patch material.
Rosen, I G; Luczak, Susan E; Weiss, Jordan
2014-03-15
We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.
Directory of Open Access Journals (Sweden)
Meleiro L.A.C.
2000-01-01
Full Text Available Most advanced computer-aided control applications rely on good dynamics process models. The performance of the control system depends on the accuracy of the model used. Typically, such models are developed by conducting off-line identification experiments on the process. These experiments for identification often result in input-output data with small output signal-to-noise ratio, and using these data results in inaccurate model parameter estimates [1]. In this work, a multivariable adaptive self-tuning controller (STC was developed for a biotechnological process application. Due to the difficulties involving the measurements or the excessive amount of variables normally found in industrial process, it is proposed to develop "soft-sensors" which are based fundamentally on artificial neural networks (ANN. A second approach proposed was set in hybrid models, results of the association of deterministic models (which incorporates the available prior knowledge about the process being modeled with artificial neural networks. In this case, kinetic parameters - which are very hard to be accurately determined in real time industrial plants operation - were obtained using ANN predictions. These methods are especially suitable for the identification of time-varying and nonlinear models. This advanced control strategy was applied to a fermentation process to produce ethyl alcohol (ethanol in industrial scale. The reaction rate considered for substratum consumption, cells and ethanol productions are validated with industrial data for typical operating conditions. The results obtained show that the proposed procedure in this work has a great potential for application.
Islam, Muhammad Rabiul; Sakib-Ul-Alam, Md.; Nazat, Kazi Kaarima; Hassan, M. Munir
2017-12-01
FEA results greatly depend on analysis parameters. MSC NASTRAN nonlinear implicit analysis code has been used in large deformation finite element analysis of pitted marine SM490A steel rectangular plate. The effect of two types actual pit shape on parameters of integrity of structure has been analyzed. For 3-D modeling, a proposed method for simulation of pitted surface by probabilistic corrosion model has been used. The result has been verified with the empirical formula proposed by finite element analysis of steel surface generated with different pitted data where analyses have been carried out by the code of LS-DYNA 971. In the both solver, an elasto-plastic material has been used where an arbitrary stress versus strain curve can be defined. In the later one, the material model is based on the J2 flow theory with isotropic hardening where a radial return algorithm is used. The comparison shows good agreement between the two results which ensures successful simulation with comparatively less energy and time.
International Nuclear Information System (INIS)
Esrick, M.A.
1981-01-01
A time-dependent, nonlinear, Schrodinger-like equation for the superconductivity order parameter is derived from the Gor'kov equations. Three types of traveling wave solutions of the equation are discussed. The phases and amplitudes of these solutions propagate at different speeds. The first type of solution has an amplitude that propagates as a soliton and it is suggested that this solution might correspond to the recently observed propagating collective modes of the order parameter. The amplitude of the second type of solution propagates as a periodic disturbance in space and time. It is suggested that this type of solution might explain the recently observed multiple values of the superconductor energy gap as well as the spatially inhomogenous superconducting state. The third type of solution, which is of a more general character, might provide some insight into non-periodic, inhomogeneous states occuring in superconductors. It is also proposed that quasiparticle injection and microwave irradiation might generate soliton-like disturbances in superconductors
Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2015-01-01
Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.
Energy Technology Data Exchange (ETDEWEB)
Verma, Dinkar, E-mail: dinkar@iitk.ac.in [Nuclear Engineering and Technology Program, Indian Institute of Technology Kanpur, Kanpur 208 016 (India); Kalra, Manjeet Singh, E-mail: drmanjeet.singh@dituniversity.edu.in [DIT University, Dehradun 248 009 (India); Wahi, Pankaj, E-mail: wahi@iitk.ac.in [Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016 (India)
2017-04-15
Highlights: • A simplified model with nonlinear void reactivity feedback is studied. • Method of multiple scales for nonlinear analysis and oscillation characteristics. • Second order void reactivity dominates in determining system dynamics. • Opposing signs of linear and quadratic void reactivity enhances global safety. - Abstract: In the present work, the effect of nonlinear void reactivity on the dynamics of a simplified lumped-parameter model for a boiling water reactor (BWR) is investigated. A mathematical model of five differential equations comprising of neutronics and thermal-hydraulics encompassing the nonlinearities associated with both the reactivity feedbacks and the heat transfer process has been used. To this end, we have considered parameters relevant to RBMK for which the void reactivity is known to be nonlinear. A nonlinear analysis of the model exploiting the method of multiple time scales (MMTS) predicts the occurrence of the two types of Hopf bifurcation, namely subcritical and supercritical, leading to the evolution of limit cycles for a range of parameters. Numerical simulations have been performed to verify the analytical results obtained by MMTS. The study shows that the nonlinear reactivity has a significant influence on the system dynamics. A parametric study with varying nominal reactor power and operating conditions in coolant channel has also been performed which shows the effect of change in concerned parameter on the boundary between regions of sub- and super-critical Hopf bifurcations in the space constituted by the two coefficients of reactivities viz. the void and the Doppler coefficient of reactivities. In particular, we find that introduction of a negative quadratic term in the void reactivity feedback significantly increases the supercritical region and dominates in determining the system dynamics.
International Nuclear Information System (INIS)
Wan, X; Xu, G H; Tao, T F; Zhang, Q; Tse, P W
2016-01-01
Most previous studies on nonlinear Lamb waves are conducted using mode pairs that satisfying strict phase velocity matching and non-zero power flux criteria. However, there are some limitations in existence. First, strict phase velocity matching is not existed in the whole frequency bandwidth; Second, excited center frequency is not always exactly equal to the true phase-velocity-matching frequency; Third, mode pairs are isolated and quite limited in number; Fourth, exciting a single desired primary mode is extremely difficult in practice and the received signal is quite difficult to process and interpret. And few attention has been paid to solving these shortcomings. In this paper, nonlinear S0 mode Lamb waves at low-frequency range satisfying approximate phase velocity matching is proposed for the purpose of overcoming these limitations. In analytical studies, the secondary amplitudes with the propagation distance considering the fundamental frequency, the maximum cumulative propagation distance (MCPD) with the fundamental frequency and the maximum linear cumulative propagation distance (MLCPD) using linear regression analysis are investigated. Based on analytical results, approximate phase velocity matching is quantitatively characterized as the relative phase velocity deviation less than a threshold value of 1%. Numerical studies are also conducted using tone burst as the excitation signal. The influences of center frequency and frequency bandwidth on the secondary amplitudes and MCPD are investigated. S1–S2 mode with the fundamental frequency at 1.8 MHz, the primary S0 mode at the center frequencies of 100 and 200 kHz are used respectively to calculate the ratios of nonlinear parameter of Al 6061-T6 to Al 7075-T651. The close agreement of the computed ratios to the actual value verifies the effectiveness of nonlinear S0 mode Lamb waves satisfying approximate phase velocity matching for characterizing the material nonlinearity. Moreover, the ratios derived
Distributions asymptotically homogeneous along the trajectories determined by one-parameter groups
International Nuclear Information System (INIS)
Drozhzhinov, Yurii N; Zav'yalov, Boris I
2012-01-01
We give a complete description of distributions that are asymptotically homogeneous (including the case of critical index of the asymptotic scale) along the trajectories determined by continuous multiplicative one-parameter transformation groups such that the real parts of all eigenvalues of the infinitesimal matrix are positive. To do this, we introduce and study special spaces of distributions. As an application of our results, we describe distributions that are homogeneous along such groups.
Directory of Open Access Journals (Sweden)
Farhad Yahgmaei
2013-01-01
Full Text Available This paper proposes different methods of estimating the scale parameter in the inverse Weibull distribution (IWD. Specifically, the maximum likelihood estimator of the scale parameter in IWD is introduced. We then derived the Bayes estimators for the scale parameter in IWD by considering quasi, gamma, and uniform priors distributions under the square error, entropy, and precautionary loss functions. Finally, the different proposed estimators have been compared by the extensive simulation studies in corresponding the mean square errors and the evolution of risk functions.
Directory of Open Access Journals (Sweden)
Anupam Pathak
2014-11-01
Full Text Available Abstract: Problem Statement: The two-parameter exponentiated Rayleigh distribution has been widely used especially in the modelling of life time event data. It provides a statistical model which has a wide variety of application in many areas and the main advantage is its ability in the context of life time event among other distributions. The uniformly minimum variance unbiased and maximum likelihood estimation methods are the way to estimate the parameters of the distribution. In this study we explore and compare the performance of the uniformly minimum variance unbiased and maximum likelihood estimators of the reliability function R(t=P(X>t and P=P(X>Y for the two-parameter exponentiated Rayleigh distribution. Approach: A new technique of obtaining these parametric functions is introduced in which major role is played by the powers of the parameter(s and the functional forms of the parametric functions to be estimated are not needed. We explore the performance of these estimators numerically under varying conditions. Through the simulation study a comparison are made on the performance of these estimators with respect to the Biasness, Mean Square Error (MSE, 95% confidence length and corresponding coverage percentage. Conclusion: Based on the results of simulation study the UMVUES of R(t and ‘P’ for the two-parameter exponentiated Rayleigh distribution found to be superior than MLES of R(t and ‘P’.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.
Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei
2017-09-21
In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.
International Nuclear Information System (INIS)
Xu, Meng; Droguett, Enrique López; Lins, Isis Didier; Chagas Moura, Márcio das
2017-01-01
The q-Weibull model is based on the Tsallis non-extensive entropy and is able to model various behaviors of the hazard rate function, including bathtub curves, by using a single set of parameters. Despite its flexibility, the q-Weibull has not been widely used in reliability applications partly because of the complicated parameters estimation. In this work, the parameters of the q-Weibull are estimated by the maximum likelihood (ML) method. Due to the intricate system of nonlinear equations, derivative-based optimization methods may fail to converge. Thus, the heuristic optimization method of artificial bee colony (ABC) is used instead. To deal with the slow convergence of ABC, it is proposed an adaptive hybrid ABC (AHABC) algorithm that dynamically combines Nelder-Mead simplex search method with ABC for the ML estimation of the q-Weibull parameters. Interval estimates for the q-Weibull parameters, including confidence intervals based on the ML asymptotic theory and on bootstrap methods, are also developed. The AHABC is validated via numerical experiments involving the q-Weibull ML for reliability applications and results show that it produces faster and more accurate convergence when compared to ABC and similar approaches. The estimation procedure is applied to real reliability failure data characterized by a bathtub-shaped hazard rate. - Highlights: • Development of an Adaptive Hybrid ABC (AHABC) algorithm for q-Weibull distribution. • AHABC combines local Nelder-Mead simplex method with ABC to enhance local search. • AHABC efficiently finds the optimal solution for the q-Weibull ML problem. • AHABC outperforms ABC and self-adaptive hybrid ABC in accuracy and convergence speed. • Useful model for reliability data with non-monotonic hazard rate.
Eleiwi, Fadi; Laleg-Kirati, Taous-Meriem
2015-01-01
This paper presents a nonlinear Lyapunov-based boundary control for the temperature difference of a membrane distillation boundary layers. The heat transfer mechanisms inside the process are modeled with a 2D advection-diffusion equation. The model
Off-line tracking of series parameters in distribution systems using AMI data
Energy Technology Data Exchange (ETDEWEB)
Williams, Tess L.; Sun, Yannan; Schneider, Kevin
2016-05-01
Electric distribution systems have historically lacked measurement points, and equipment is often operated to its failure point, resulting in customer outages. The widespread deployment of sensors at the distribution level is enabling observability. This paper presents an off-line parameter value tracking procedure that takes advantage of the increasing number of measurement devices being deployed at the distribution level to estimate changes in series impedance parameter values over time. The tracking of parameter values enables non-diurnal and non-seasonal change to be flagged for investigation. The presented method uses an unbalanced Distribution System State Estimation (DSSE) and a measurement residual-based parameter estimation procedure. Measurement residuals from multiple measurement snapshots are combined in order to increase the effective local redundancy and improve the robustness of the calculations in the presence of measurement noise. Data from devices on the primary distribution system and from customer meters, via an AMI system, form the input data set. Results of simulations on the IEEE 13-Node Test Feeder are presented to illustrate the proposed approach applied to changes in series impedance parameters. A 5% change in series resistance elements can be detected in the presence of 2% measurement error when combining less than 1 day of measurement snapshots into a single estimate.
Probabilistic analysis of glass elements with three-parameter Weibull distribution
International Nuclear Information System (INIS)
Ramos, A.; Muniz-Calvente, M.; Fernandez, P.; Fernandez Cantel, A.; Lamela, M. J.
2015-01-01
Glass and ceramics present a brittle behaviour so a large scatter in the test results is obtained. This dispersion is mainly due to the inevitable presence of micro-cracks on its surface, edge defects or internal defects, which must be taken into account using an appropriate failure criteria non-deterministic but probabilistic. Among the existing probability distributions, the two or three parameter Weibull distribution is generally used in adjusting material resistance results, although the method of use thereof is not always correct. Firstly, in this work, the results of a large experimental programme using annealed glass specimens of different dimensions based on four-point bending and coaxial double ring tests was performed. Then, the finite element models made for each type of test, the adjustment of the parameters of the three-parameter Weibull distribution function (cdf) (λ: location, β: shape, d: scale) for a certain failure criterion and the calculation of the effective areas from the cumulative distribution function are presented. Summarizing, this work aims to generalize the use of the three-parameter Weibull function in structural glass elements with stress distributions not analytically described, allowing to apply the probabilistic model proposed in general loading distributions. (Author)
Directory of Open Access Journals (Sweden)
R. Talebitooti
Full Text Available In this paper the effect of quadratic and cubic non-linearities of the system consisting of the crankshaft and torsional vibration damper (TVD is taken into account. TVD consists of non-linear elastomer material used for controlling the torsional vibration of crankshaft. The method of multiple scales is used to solve the governing equations of the system. Meanwhile, the frequency response of the system for both harmonic and sub-harmonic resonances is extracted. In addition, the effects of detuning parameters and other dimensionless parameters for a case of harmonic resonance are investigated. Moreover, the external forces including both inertia and gas forces are simultaneously applied into the model. Finally, in order to study the effectiveness of the parameters, the dimensionless governing equations of the system are solved, considering the state space method. Then, the effects of the torsional damper as well as all corresponding parameters of the system are discussed.
Kar, Soummya; Moura, José M. F.
2011-08-01
The paper considers gossip distributed estimation of a (static) distributed random field (a.k.a., large scale unknown parameter vector) observed by sparsely interconnected sensors, each of which only observes a small fraction of the field. We consider linear distributed estimators whose structure combines the information \\emph{flow} among sensors (the \\emph{consensus} term resulting from the local gossiping exchange among sensors when they are able to communicate) and the information \\emph{gathering} measured by the sensors (the \\emph{sensing} or \\emph{innovations} term.) This leads to mixed time scale algorithms--one time scale associated with the consensus and the other with the innovations. The paper establishes a distributed observability condition (global observability plus mean connectedness) under which the distributed estimates are consistent and asymptotically normal. We introduce the distributed notion equivalent to the (centralized) Fisher information rate, which is a bound on the mean square error reduction rate of any distributed estimator; we show that under the appropriate modeling and structural network communication conditions (gossip protocol) the distributed gossip estimator attains this distributed Fisher information rate, asymptotically achieving the performance of the optimal centralized estimator. Finally, we study the behavior of the distributed gossip estimator when the measurements fade (noise variance grows) with time; in particular, we consider the maximum rate at which the noise variance can grow and still the distributed estimator being consistent, by showing that, as long as the centralized estimator is consistent, the distributed estimator remains consistent.
Shuguang Liua; Pamela Anderson; Guoyi Zhoud; Boone Kauffman; Flint Hughes; David Schimel; Vicente Watson; Joseph. Tosi
2008-01-01
Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in...
Distributed and decentralized state estimation in gas networks as distributed parameter systems.
Ahmadian Behrooz, Hesam; Boozarjomehry, R Bozorgmehry
2015-09-01
In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline networks. In the construction of local models, due to the existence of common states and interconnections among the subsystems, the assimilation and prediction steps of the Kalman filter are modified to take the overlapping and external states into account. However, dynamic Riccati equation for each subsystem is constructed based on the local model, which introduces a maximum error of 5% in the estimated standard deviation of the states in the benchmarks studied in this paper. The performance of the proposed methodology has been shown based on the comparison of its accuracy and computational demands against their counterparts in centralized Kalman filter for two viable benchmarks. In a real life network, it is shown that while the accuracy is not significantly decreased, the real-time factor of the state estimation is increased by a factor of 10. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Lake, Spencer P; Miller, Kristin S; Elliott, Dawn M; Soslowsky, Louis J
2009-12-01
Tendon exhibits nonlinear stress-strain behavior that may be partly due to movement of collagen fibers through the extracellular matrix. While a few techniques have been developed to evaluate the fiber architecture of other soft tissues, the organizational behavior of tendon under load has not been determined. The supraspinatus tendon (SST) of the rotator cuff is of particular interest for investigation due to its complex mechanical environment and corresponding inhomogeneity. In addition, SST injury occurs frequently with limited success in treatment strategies, illustrating the need for a better understanding of SST properties. Therefore, the objective of this study was to quantitatively evaluate the inhomogeneous tensile mechanical properties, fiber organization, and fiber realignment under load of human SST utilizing a novel polarized light technique. Fiber distributions were found to become more aligned under load, particularly during the low stiffness toe-region, suggesting that fiber realignment may be partly responsible for observed nonlinear behavior. Fiber alignment was found to correlate significantly with mechanical parameters, providing evidence for strong structure-function relationships in tendon. Human SST exhibits complex, inhomogeneous mechanical properties and fiber distributions, perhaps due to its complex loading environment. Surprisingly, histological grade of degeneration did not correlate with mechanical properties.
Malyarenko, Dariya I; Pang, Yuxi; Senegas, Julien; Ivancevic, Marko K; Ross, Brian D; Chenevert, Thomas L
2015-12-01
Spatially non-uniform diffusion weighting bias due to gradient nonlinearity (GNL) causes substantial errors in apparent diffusion coefficient (ADC) maps for anatomical regions imaged distant from magnet isocenter. Our previously-described approach allowed effective removal of spatial ADC bias from three orthogonal DWI measurements for mono-exponential media of arbitrary anisotropy. The present work evaluates correction feasibility and performance for quantitative diffusion parameters of the two-component IVIM model for well-perfused and nearly isotropic renal tissue. Sagittal kidney DWI scans of a volunteer were performed on a clinical 3T MRI scanner near isocenter and offset superiorly. Spatially non-uniform diffusion weighting due to GNL resulted both in shift and broadening of perfusion-suppressed ADC histograms for off-center DWI relative to unbiased measurements close to isocenter. Direction-average DW-bias correctors were computed based on the known gradient design provided by vendor. The computed bias maps were empirically confirmed by coronal DWI measurements for an isotropic gel-flood phantom. Both phantom and renal tissue ADC bias for off-center measurements was effectively removed by applying pre-computed 3D correction maps. Comparable ADC accuracy was achieved for corrections of both b -maps and DWI intensities in presence of IVIM perfusion. No significant bias impact was observed for IVIM perfusion fraction.
Directory of Open Access Journals (Sweden)
Jaroszewicz Jerzy
2018-01-01
Full Text Available The work is devoted to methods of analysis of vibrations and stability of discrete-continuous, multi-parameter models of beams, shafts, rotors, vanes, converting to homogeneous and one-dimensional. The properties of Cauchy's influence function and the characteristic series method were used to solve the boundary problem. It has been shown that the methods are an effective tool for solving boundary problems described by ordinary fourth-and second-order differential equations with variable parameters. Particular attention should be paid to the solution of the border problem of two-parameter elastic systems with variable distribution of parameters. Universal beam-specific equations with typical support conditions including vertical support, which do not depend on beam shape and axial load type, are recorded. The shape and type of load are considered in the form of an impact function that corresponds to any change in cross-section of the support and continuous axial load, so that the functions describing the stiffness, the mass and the continuous load are complete. As a result of the solution of the boundary vibration problem of freely bent support and any change in its cross-section, loaded with any longitudinal load, arranged on the resilient substrate, strict relations between the own frequency parameters and the load parameters were derived. Using the methods, simple calculations were made, easy to use in engineering practice and conditions of use were given. Experimental studies have confirmed the high accuracy of theoretical calculations using the proposed methods and formulas.
Directory of Open Access Journals (Sweden)
Ling Kang
Full Text Available Heuristic search algorithms, which are characterized by faster convergence rates and can obtain better solutions than the traditional mathematical methods, are extensively used in engineering optimizations. In this paper, a newly developed elitist-mutated particle swarm optimization (EMPSO technique and an improved gravitational search algorithm (IGSA are successively applied to parameter estimation problems of Muskingum flood routing models. First, the global optimization performance of the EMPSO and IGSA are validated by nine standard benchmark functions. Then, to further analyse the applicability of the EMPSO and IGSA for various forms of Muskingum models, three typical structures are considered: the basic two-parameter linear Muskingum model (LMM, a three-parameter nonlinear Muskingum model (NLMM and a four-parameter nonlinear Muskingum model which incorporates the lateral flow (NLMM-L. The problems are formulated as optimization procedures to minimize the sum of the squared deviations (SSQ or the sum of the absolute deviations (SAD between the observed and the estimated outflows. Comparative results of the selected numerical cases (Case 1-3 show that the EMPSO and IGSA not only rapidly converge but also obtain the same best optimal parameter vector in every run. The EMPSO and IGSA exhibit superior robustness and provide two efficient alternative approaches that can be confidently employed to estimate the parameters of both linear and nonlinear Muskingum models in engineering applications.
Directory of Open Access Journals (Sweden)
Streck Nereu Augusto
2003-01-01
Full Text Available Temperature is a major factor that affects metabolic processes in living organisms. Thermal time has been widely used to account for the effects of temperature on crop growth and development. However, the thermal time approach has been criticized because it assumes a linear relationship between the rate of crop growth or development and temperature. The response of the rate of crop growth and development to temperature is nonlinear. The objective of this study was to develop a generalized nonlinear temperature response function for some growth and developmental parameters in kiwifruit (Actinidia deliciosa (A. Chev. C. F. Liang & A. R. Ferguson. The nonlinear function has three coefficients (the cardinal temperatures, which were 0ºC, 25ºC, and 40ºC. Data of temperature response of relative growth rate, relative leaf area growth, net photosynthesis rate, and leaf appearance rate in kiwifruit (female cv. Hayward at two light levels, which are from published research, were used as independent data for evaluating the performance of the nonlinear and the thermal time functions. The results showed that the generalized nonlinear response function is better than the thermal time approach, and the temperature response of several growth and developmental parameters in kiwifruit can be described with the same response function.
Pramodini, S.; Poornesh, P.
2014-10-01
We report the studies on third-order optical nonlinearity and optical limiting of anthraquinone dyes. Z-scan technique was employed to evaluate the nonlinear parameters such as nonlinear absorption coefficient βeff and nonlinear index of refraction n2. Continuous wave He-Ne laser was used as the source of excitation. The estimated values of βeff, n2 and χ(3) are of the order of 10-3 cm/W, 10-5 esu and 10-7 esu respectively. The presence of donor and acceptor groups in the structure results in increase in conjugation length. This resulted in the enhancement of nonlinear optical parameters values of the dye. Multiple diffraction rings were observed when the samples were exposed to laser beam due to thermal lensing. Dyes exhibited good optical limiting behavior under the experimental conditions. The results indicate that the dyes investigated here are materialise as candidates for photonics device applications such as optical power limiters.
Zalvidea; Colautti; Sicre
2000-05-01
An analysis of the Strehl ratio and the optical transfer function as imaging quality parameters of optical elements with enhanced focal length is carried out by employing the Wigner distribution function. To this end, we use four different pupil functions: a full circular aperture, a hyper-Gaussian aperture, a quartic phase plate, and a logarithmic phase mask. A comparison is performed between the quality parameters and test images formed by these pupil functions at different defocus distances.
Directory of Open Access Journals (Sweden)
Azam Zaka
2014-10-01
Full Text Available This paper is concerned with the modifications of maximum likelihood, moments and percentile estimators of the two parameter Power function distribution. Sampling behavior of the estimators is indicated by Monte Carlo simulation. For some combinations of parameter values, some of the modified estimators appear better than the traditional maximum likelihood, moments and percentile estimators with respect to bias, mean square error and total deviation.
Directory of Open Access Journals (Sweden)
Shujing Su
2015-01-01
Full Text Available For the characteristics of parameters dispersion in large factories, storehouses, and other applications, a distributed parameter measurement system is designed that is based on the ring network. The structure of the system and the circuit design of the master-slave node are described briefly. The basic protocol architecture about transmission communication is introduced, and then this paper comes up with two kinds of distributed transmission control methods. Finally, the reliability, extendibility, and control characteristic of these two methods are tested through a series of experiments. Moreover, the measurement results are compared and discussed.
Distribution and Parameter's Calculations of Television Cameras Inside a Nuclear Facility
International Nuclear Information System (INIS)
El-kafas, A.A.
2009-01-01
In this work, a distribution of television cameras and parameter's calculation inside and outside a nuclear facility is presented. Each of exterior and interior camera systems will be described and explained. The work shows the overall closed circuit television system. Fixed and moving cameras with various lens format and different angles of view are used. The calculations of width of images sensitive area and Lens focal length for the cameras will be introduced. The work shows the camera locations and distributions inside and outside the nuclear facility. The technical specifications and parameters for cameras selection are tabulated
A Note on Parameter Estimation in the Composite Weibull–Pareto Distribution
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Enrique Calderín-Ojeda
2018-02-01
Full Text Available Composite models have received much attention in the recent actuarial literature to describe heavy-tailed insurance loss data. One of the models that presents a good performance to describe this kind of data is the composite Weibull–Pareto (CWL distribution. On this note, this distribution is revisited to carry out estimation of parameters via mle and mle2 optimization functions in R. The results are compared with those obtained in a previous paper by using the nlm function, in terms of analytical and graphical methods of model selection. In addition, the consistency of the parameter estimation is examined via a simulation study.
Xiang, Yang; Luo, Yiyang; Zhang, Wei; Liu, Deming; Sun, Qizhen
2017-04-01
We propose and demonstrate a distributed fiber sensor based on cascaded microfiber Fabry-Perot interferometers (MFPI) for simultaneous refractive index (SRI) and temperature measurement. By employing MFPI which is fabricated by taper-drawing the center of a uniform fiber Bragg grating (FBG) on standard fiber into a section of microfiber, dual parameters including SRI and temperature can be detected through demodulating the reflection spectrum of the MFPI. Further, wavelength-division-multiplexing (WDM) is applied to realize distributed dual-parameter fiber sensor by using cascaded MFPIs with different Bragg wavelengths. A prototype sensor system with 5 cascaded MFPIs is constructed to experimentally demonstrate the sensing performance.
Artemyev, Anton V.; Neishtadt, Anatoly I.; Vasiliev, Alexei A.
2018-04-01
Accurately modelling and forecasting of the dynamics of the Earth's radiation belts with the available computer resources represents an important challenge that still requires significant advances in the theoretical plasma physics field of wave-particle resonant interaction. Energetic electron acceleration or scattering into the Earth's atmosphere are essentially controlled by their resonances with electromagnetic whistler mode waves. The quasi-linear diffusion equation describes well this resonant interaction for low intensity waves. During the last decade, however, spacecraft observations in the radiation belts have revealed a large number of whistler mode waves with sufficiently high intensity to interact with electrons in the nonlinear regime. A kinetic equation including such nonlinear wave-particle interactions and describing the long-term evolution of the electron distribution is the focus of the present paper. Using the Hamiltonian theory of resonant phenomena, we describe individual electron resonance with an intense coherent whistler mode wave. The derived characteristics of such a resonance are incorporated into a generalized kinetic equation which includes non-local transport in energy space. This transport is produced by resonant electron trapping and nonlinear acceleration. We describe the methods allowing the construction of nonlinear resonant terms in the kinetic equation and discuss possible applications of this equation.
Directory of Open Access Journals (Sweden)
Yu-E Song
2014-01-01
Full Text Available The Wigner-Ville distribution (WVD based on the linear canonical transform (LCT (WDL not only has the advantages of the LCT but also has the good properties of WVD. In this paper, some new and important properties of the WDL are derived, and the relationships between WDL and some other time-frequency distributions are discussed, such as the ambiguity function based on LCT (LCTAF, the short-time Fourier transform (STFT, and the wavelet transform (WT. The WDLs of some signals are also deduced. A novel definition of the WVD based on the LCT and generalized instantaneous autocorrelation function (GWDL is proposed and its applications in the estimation of parameters for QFM signals are also discussed. The GWDL of the QFM signal generates an impulse and the third-order phase coefficient of QFM signal can be estimated in accordance with the position information of such impulse. The proposed algorithm is fast because it only requires 1-dimensional maximization. Also the new algorithm only has fourth-order nonlinearity thus it has accurate estimation and low signal-to-noise ratio (SNR threshold. The simulation results are provided to support the theoretical results.
Exact run length distribution of the double sampling x-bar chart with estimated process parameters
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Teoh, W. L.
2016-05-01
Full Text Available Since the run length distribution is generally highly skewed, a significant concern about focusing too much on the average run length (ARL criterion is that we may miss some crucial information about a control chart’s performance. Thus it is important to investigate the entire run length distribution of a control chart for an in-depth understanding before implementing the chart in process monitoring. In this paper, the percentiles of the run length distribution for the double sampling (DS X chart with estimated process parameters are computed. Knowledge of the percentiles of the run length distribution provides a more comprehensive understanding of the expected behaviour of the run length. This additional information includes the early false alarm, the skewness of the run length distribution, and the median run length (MRL. A comparison of the run length distribution between the optimal ARL-based and MRL-based DS X chart with estimated process parameters is presented in this paper. Examples of applications are given to aid practitioners to select the best design scheme of the DS X chart with estimated process parameters, based on their specific purpose.
Xu, Jingping; Tripathy, Sakya; Rubin, Jonathan M; Stidham, Ryan W; Johnson, Laura A; Higgins, Peter D R; Kim, Kang
2012-03-01
Strain developed under quasi-static deformation has been mostly used in ultrasound elasticity imaging (UEI) to determine the stiffness change of tissues. However, the strain measure in UEI is often less sensitive to a subtle change of stiffness. This is particularly true for Crohn's disease where we have applied strain imaging to the differentiation of acutely inflamed bowel from chronically fibrotic bowel. In this study, a new nonlinear elastic parameter of the soft tissues is proposed to overcome this limit. The purpose of this study is to evaluate the newly proposed method and demonstrate its feasibility in the UEI. A nonlinear characteristic of soft tissues over a relatively large dynamic range of strain was investigated. A simplified tissue model based on a finite element (FE) analysis was integrated with a laboratory developed ultrasound radio-frequency (RF) signal synthesis program. Two-dimensional speckle tracking was applied to this model to simulate the nonlinear behavior of the strain developed in a target inclusion over the applied average strain to the surrounding tissues. A nonlinear empirical equation was formulated and optimized to best match the developed strain-to-applied strain relation obtained from the FE simulation. The proposed nonlinear equation was applied to in vivo measurements and nonlinear parameters were further empirically optimized. For an animal model, acute and chronic inflammatory bowel disease was induced in Lewis rats with trinitrobenzene sulfonic acid (TNBS)-ethanol treatments. After UEI, histopathology and direct mechanical measurements were performed on the excised tissues. The extracted nonlinear parameter from the developed strain-to-applied strain relation differentiated the three different tissue types with 1.96 ± 0.12 for normal, 1.50 ± 0.09 for the acutely inflamed and 1.03 ± 0.08 for the chronically fibrotic tissue. T-tests determined that the nonlinear parameters between normal, acutely inflamed and fibrotic tissue
SU-E-T-113: Dose Distribution Using Respiratory Signals and Machine Parameters During Treatment
International Nuclear Information System (INIS)
Imae, T; Haga, A; Saotome, N; Kida, S; Nakano, M; Takeuchi, Y; Shiraki, T; Yano, K; Yamashita, H; Nakagawa, K; Ohtomo, K
2014-01-01
Purpose: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. Treatment plans for lung tumors using stereotactic body radiotherapy (SBRT) are calculated with planning computed tomography (CT) images only exhale phase. Purpose of this study is to evaluate dose distribution by reconstructing from only the data such as respiratory signals and machine parameters acquired during treatment. Methods: Phantom and three patients with lung tumor underwent CT scans for treatment planning. They were treated by VMAT while acquiring projection images to derive their respiratory signals and machine parameters including positions of multi leaf collimators, dose rates and integrated monitor units. The respiratory signals were divided into 4 and 10 phases and machine parameters were correlated with the divided respiratory signals based on the gantry angle. Dose distributions of each respiratory phase were calculated from plans which were reconstructed from the respiratory signals and the machine parameters during treatment. The doses at isocenter, maximum point and the centroid of target were evaluated. Results and Discussion: Dose distributions during treatment were calculated using the machine parameters and the respiratory signals detected from projection images. Maximum dose difference between plan and in treatment distribution was −1.8±0.4% at centroid of target and dose differences of evaluated points between 4 and 10 phases were no significant. Conclusion: The present method successfully evaluated dose distribution using respiratory signals and machine parameters during treatment. This method is feasible to verify the actual dose for moving target
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available A procedure for calculation of refrigerant mass flow rate is implemented in the distributed numerical model to simulate the flow in finned-tube coil dry-expansion evaporators, usually found in refrigeration and air-conditioning systems. Two-phase refrigerant flow inside the tubes is assumed to be one-dimensional, unsteady, and homogeneous. In the model the effects of refrigerant pressure drop and the moisture condensation from the air flowing over the external surface of the tubes are considered. The results obtained are the distributions of refrigerant velocity, temperature and void fraction, tube-wall temperature, air temperature, and absolute humidity. The finite volume method is used to discretize the governing equations. Additionally, given the operation conditions and the geometric parameters, the model allows the calculation of the refrigerant mass flow rate. The value of mass flow rate is computed using the process of parameter estimation with the minimization method of Levenberg-Marquardt minimization. In order to validate the developed model, the obtained results using HFC-134a as a refrigerant are compared with available data from the literature.
International Nuclear Information System (INIS)
Oezyurt, N.N.
2002-01-01
Groundwater's residence time distribution is an important information to identify the transport mechanism in aquifer systems. In the absence or scarcity of geometric, hydraulic and geohydrologic data needed to describe a flow system, lumped parameter models, that handle the flow system as a whole, exist as an alternative to determine the residence time distribution. Lumped parametre models comprise of idealized models of piston and well-mixed flow and their combinations. Aquifer properties such as, dead volume and by-pass flow can also be included in these models. With the aid of these models, conceptual aquifer models can be tested and residence time distribution of groundwater can be determined
National Research Council Canada - National Science Library
Drazin, P. G
1992-01-01
This book is an introduction to the theories of bifurcation and chaos. It treats the solution of nonlinear equations, especially difference and ordinary differential equations, as a parameter varies...
International Nuclear Information System (INIS)
Niemiec, W.
1985-01-01
In the literature of distributed parameter modelling of real processes is not considered the class of multicomponent chemical processes in gas, fluid and solid phase. The aim of paper is constitutive distributed parameter physicochemical model, constructed on kinetics and phenomenal analysis of multicomponent chemical processes in gas, fluid and solid phase. The mass, energy and momentum aspects of these multicomponent chemical reactions and adequate phenomena are utilized in balance operations, by conditions of: constitutive invariance for continuous media with space and time memories, reciprocity principle for isotropic and anisotropic nonhomogeneous media with space and time memories, application of definitions of following derivative and equation of continuity, to the construction of systems of partial differential constitutive state equations, in the following derivative forms for gas, fluid and solid phase. Couched in this way all physicochemical conditions of multicomponent chemical processes in gas, fluid and solid phase are new form of constitutive distributed parameter model for automatics and its systems of equations are new form of systems of partial differential constitutive state equations in sense of phenomenal distributed parameter control
Eliciting hyperparameters of prior distributions for the parameters of paired comparison models
Directory of Open Access Journals (Sweden)
Nasir Abbas
2013-02-01
Full Text Available Normal 0 false false false EN-US X-NONE AR-SA In the study of paired comparisons (PC, items may be ranked or issues may be prioritized through subjective assessment of certain judges. PC models are developed and then used to serve the purpose of ranking. The PC models may be studied through classical or Bayesian approach. Bayesian inference is a modern statistical technique used to draw conclusions about the population parameters. Its beauty lies in incorporating prior information about the parameters into the analysis in addition to current information (i.e. data. The prior and current information are formally combined to yield a posterior distribution about the population parameters, which is the work bench of the Bayesian statisticians. However, the problems the Bayesians face correspond to the selection and formal utilization of prior distribution. Once the type of prior distribution is decided to be used, the problem of estimating the parameters of the prior distribution (i.e. elicitation still persists. Different methods are devised to serve the purpose. In this study an attempt is made to use Minimum Chi-square (hence forth MCS for the elicitation purpose. Though it is a classical estimation technique, but is used here for the election purpose. The entire elicitation procedure is illustrated through a numerical data set.
Effects of abdominal fat distribution parameters on severity of acute pancreatitis.
LENUS (Irish Health Repository)
O'Leary, D P
2012-07-01
Obesity is a well-established risk factor for acute pancreatitis. Increased visceral fat has been shown to exacerbate the pro-inflammatory milieu experienced by patients. This study aimed to investigate the relationship between the severity of acute pancreatitis and abdominal fat distribution parameters measured on computed tomography (CT) scan.
The values of the parameters of some multilayer distributed RC null networks
Huelsman, L. P.; Raghunath, S.
1974-01-01
In this correspondence, the values of the parameters of some multilayer distributed RC notch networks are determined, and the usually accepted values are shown to be in error. The magnitude of the error is illustrated by graphs of the frequency response of the networks.
Directory of Open Access Journals (Sweden)
N. K. Sajeevkumar
2014-09-01
Full Text Available In this article, we derived the Best Linear Unbiased Estimator (BLUE of the location parameter of certain distributions with known coefficient of variation by record values. Efficiency comparisons are also made on the proposed estimator with some of the usual estimators. Finally we give a real life data to explain the utility of results developed in this article.
On the control of distributed parameter systems using a multidimensional systems setting
Czech Academy of Sciences Publication Activity Database
Cichy, B.; Augusta, Petr; Rogers, E.; Galkowski, K.; Hurák, Z.
2008-01-01
Roč. 22, č. 7 (2008), s. 1566-1581 ISSN 0888-3270 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : Distributed parameter systems * Modelling * Control law design Subject RIV: BC - Control Systems Theory Impact factor: 1.984, year: 2008
International Nuclear Information System (INIS)
Xing Dianchuan; Yan Changqi; Sun Licheng; Liu Jingyu
2013-01-01
Experimental study on characteristics of interfacial parameter distribution for air-water bubbly flow in an inclined circular tube was performed by using the double sensor probe method. Parameters including radial distributions of local void fraction, bubble passing frequency, interfacial area concentration and bubble equivalent diameter were measured using the probe. The inner diameter of test section is 50 mm, and the liquid superficial velocity is 0.144 m/s, with the gas superficial velocity ranging from 0 to 0.054 m/is. The results show that bubbles obviously move toward the upper wall and congregate. The local interfacial area concentration, bubble passing frequency and void fraction have similar radial distribution profiles. Different from the vertical condition, for a cross-sectional area of the test section, the peak value near the upper side increases, while decreases or even disappears near the underside. The local parameter increases as the radial positions change from lower to upper location, and the increased slope becomes larger as the inclination angles increase. The equivalent bubble diameter doesn't vary with radial position, superficial gas velocity and inclination angle, and bubble aggregation and breaking up nearly doesn't occur. The mechanism of effects of inclination on local parameter distribution for bubbly flow is explained by analyzing the transverse force governing the bubble motion. (authors)
International Nuclear Information System (INIS)
Capeluto, W.; Campos, T. de los
2010-01-01
The aim of this paper is to analyze the distribution of textural statistical parameters and spatial variation in the morphology of the sediment areas. The geology of the area comprises alluvial and alluvial deposits of variable thicknesses overlying deposits of Fray Bent os, Salto and Guichon formations that occasionally emerge in the river bed
Robust control of distributed parameter mechanical systems using a multidimensional systems approach
Czech Academy of Sciences Publication Activity Database
Cichy, B.; Augusta, Petr; Rogers, E.; Galkowski, K.; Hurák, Z.
2010-01-01
Roč. 58, č. 1 (2010), s. 67-75 ISSN 0239-7269 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : robust control * distributed parameter mechanical systems * multidimensional systems Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2010/TR/augusta-0347866.pdf
An EOQ Model with Two-Parameter Weibull Distribution Deterioration and Price-Dependent Demand
Mukhopadhyay, Sushanta; Mukherjee, R. N.; Chaudhuri, K. S.
2005-01-01
An inventory replenishment policy is developed for a deteriorating item and price-dependent demand. The rate of deterioration is taken to be time-proportional and the time to deterioration is assumed to follow a two-parameter Weibull distribution. A power law form of the price dependence of demand is considered. The model is solved analytically…
Effects of vortex-like and non-thermal ion distributions on non-linear dust-acoustic waves
International Nuclear Information System (INIS)
Mamun, A.A.; Cairns, R.A.; Shukla, P.K.
1996-01-01
The effects of vortex-like and non-thermal ion distributions are incorporated in the study of nonlinear dust-acoustic waves in an unmagnetized dusty plasma. It is found that owing to the departure from the Boltzmann ion distribution to a vortex-like phase space distribution, the dynamics of small but finite amplitude dust-acoustic waves is governed by a modified Kortweg endash de Vries equation. The latter admits a stationary dust-acoustic solitary wave solution, which has larger amplitude, smaller width, and higher propagation velocity than that involving adiabatic ions. On the other hand, consideration of a non-thermal ion distribution provides the possibility of coexistence of large amplitude rarefactive as well as compressive dust-acoustic solitary waves, whereas these structures appear independently when the wave amplitudes become infinitely small. The present investigation should help us to understand the salient features of the non-linear dust-acoustic waves that have been observed in a recent numerical simulation study. copyright 1996 American Institute of Physics
More, Anand Govind; Gupta, Sunil Kumar
2018-03-24
Bioelectrochemical system (BES) is a novel, self-sustaining metal removal technology functioning on the utilization of chemical energy of organic matter with the help of microorganisms. Experimental trials of two chambered BES reactor were conducted with varying substrate concentration using sodium acetate (500 mg/L to 2000 mg/L COD) and different initial chromium concentration (Cr i ) (10-100 mg/L) at different cathode pH (pH 1-7). In the current study mathematical models based on multiple linear regression (MLR) and non-linear regression (NLR) approach were developed using laboratory experimental data for determining chromium removal efficiency (CRE) in the cathode chamber of BES. Substrate concentration, rate of substrate consumption, Cr i , pH, temperature and hydraulic retention time (HRT) were the operating process parameters of the reactor considered for development of the proposed models. MLR showed a better correlation coefficient (0.972) as compared to NLR (0.952). Validation of the models using t-test analysis revealed unbiasedness of both the models, with t critical value (2.04) greater than t-calculated values for MLR (-0.708) and NLR (-0.86). The root-mean-square error (RMSE) for MLR and NLR were 5.06 % and 7.45 %, respectively. Comparison between both models suggested MLR to be best suited model for predicting the chromium removal behavior using the BES technology to specify a set of operating conditions for BES. Modelling the behavior of CRE will be helpful for scale up of BES technology at industrial level. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Figueroa-O'Farrill, J.M.; Mas, J.; Ramos, E.
1993-01-01
The KP hierarchy is hamiltonian relative to a one-parameter family of Poisson structures obtained from a generalized Adler map in the space of formal pseudodifferential symbols with noninteger powers. The resulting W-algebra is a one-parameter deformation of W KP admitting a central extension for generic values of the parameter, reducing naturally to W n for special values of the parameter, and contracting to the centrally extended W 1+∞ , W ∞ and further truncations. In the classical limit, all algebras in the one-parameter family are equivalent and isomorphic to W KP . The reduction induced by setting the spin-one field to zero yields a one-parameter deformation of W ∞ which contracts to a new nonlinear algebra of the W ∞ -type. (orig.)
Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions
Liu, C.; Charpentier, R.R.; Su, J.
2011-01-01
Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log-geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log-geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log-geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters. ?? 2011 International Association for Mathematical Geosciences.
Identification of Synchronous Generator Electric Parameters Connected to the Distribution Grid
Directory of Open Access Journals (Sweden)
Frolov M. Yu.
2017-04-01
Full Text Available According to modern trends, the power grids with distributed generation will have an open system architecture. It means that active consumers, owners of distributed power units, including mobile units, must have free access to the grid, like when using internet, so it is necessary to have plug and play technologies. Thanks to them, the system will be able to identify the unit type and the unit parameters. Therefore, the main aim of research, described in the paper, was to develop and research a new method of electric parameters identification of synchronous generator. The main feature of the proposed method is that parameter identification is performed while the generator to the grid, so it fits in the technological process of operation of the machine and does not influence on the connection time of the machine. For the implementation of the method, it is not necessary to create dangerous operation modes for the machine or to have additional expensive equipment and it can be used for salient pole machines and round rotor machines. The parameter identification accuracy can be achieved by more accurate account of electromechanical transient process, and making of overdetermined system with many more numbers of equations. Parameter identification will be made with each generator connection to the grid. Comparing data obtained from each connection, the middle values can be find by numerical method, and thus, each subsequent identification will accurate the machine parameters.
A "total parameter estimation" method in the varification of distributed hydrological models
Wang, M.; Qin, D.; Wang, H.
2011-12-01
Conventionally hydrological models are used for runoff or flood forecasting, hence the determination of model parameters are common estimated based on discharge measurements at the catchment outlets. With the advancement in hydrological sciences and computer technology, distributed hydrological models based on the physical mechanism such as SWAT, MIKESHE, and WEP, have gradually become the mainstream models in hydrology sciences. However, the assessments of distributed hydrological models and model parameter determination still rely on runoff and occasionally, groundwater level measurements. It is essential in many countries, including China, to understand the local and regional water cycle: not only do we need to simulate the runoff generation process and for flood forecasting in wet areas, we also need to grasp the water cycle pathways and consumption process of transformation in arid and semi-arid regions for the conservation and integrated water resources management. As distributed hydrological model can simulate physical processes within a catchment, we can get a more realistic representation of the actual water cycle within the simulation model. Runoff is the combined result of various hydrological processes, using runoff for parameter estimation alone is inherits problematic and difficult to assess the accuracy. In particular, in the arid areas, such as the Haihe River Basin in China, runoff accounted for only 17% of the rainfall, and very concentrated during the rainy season from June to August each year. During other months, many of the perennial rivers within the river basin dry up. Thus using single runoff simulation does not fully utilize the distributed hydrological model in arid and semi-arid regions. This paper proposed a "total parameter estimation" method to verify the distributed hydrological models within various water cycle processes, including runoff, evapotranspiration, groundwater, and soil water; and apply it to the Haihe river basin in
Mat Jan, Nur Amalina; Shabri, Ani
2017-01-01
TL-moments approach has been used in an analysis to identify the best-fitting distributions to represent the annual series of maximum streamflow data over seven stations in Johor, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: Three-parameter lognormal (LN3) and Pearson Type III (P3) distribution. The main objective of this study is to derive the TL-moments ( t 1,0), t 1 = 1,2,3,4 methods for LN3 and P3 distributions. The performance of TL-moments ( t 1,0), t 1 = 1,2,3,4 was compared with L-moments through Monte Carlo simulation and streamflow data over a station in Johor, Malaysia. The absolute error is used to test the influence of TL-moments methods on estimated probability distribution functions. From the cases in this study, the results show that TL-moments with four trimmed smallest values from the conceptual sample (TL-moments [4, 0]) of LN3 distribution was the most appropriate in most of the stations of the annual maximum streamflow series in Johor, Malaysia.
Wang, Yujuan; Song, Yongduan; Ren, Wei
2017-07-06
This paper presents a distributed adaptive finite-time control solution to the formation-containment problem for multiple networked systems with uncertain nonlinear dynamics and directed communication constraints. By integrating the special topology feature of the new constructed symmetrical matrix, the technical difficulty in finite-time formation-containment control arising from the asymmetrical Laplacian matrix under single-way directed communication is circumvented. Based upon fractional power feedback of the local error, an adaptive distributed control scheme is established to drive the leaders into the prespecified formation configuration in finite time. Meanwhile, a distributed adaptive control scheme, independent of the unavailable inputs of the leaders, is designed to keep the followers within a bounded distance from the moving leaders and then to make the followers enter the convex hull shaped by the formation of the leaders in finite time. The effectiveness of the proposed control scheme is confirmed by the simulation.
Non-linear singular problems in p-adic analysis: associative algebras of p-adic distributions
International Nuclear Information System (INIS)
Albeverio, S; Khrennikov, A Yu; Shelkovich, V M
2005-01-01
We propose an algebraic theory which can be used for solving both linear and non-linear singular problems of p-adic analysis related to p-adic distributions (generalized functions). We construct the p-adic Colombeau-Egorov algebra of generalized functions, in which Vladimirov's pseudo-differential operator plays the role of differentiation. This algebra is closed under Fourier transformation and associative convolution. Pointvalues of generalized functions are defined, and it turns out that any generalized function is uniquely determined by its pointvalues. We also construct an associative algebra of asymptotic distributions, which is generated by the linear span of the set of associated homogeneous p-adic distributions. This algebra is embedded in the Colombeau-Egorov algebra as a subalgebra. In addition, a new technique for constructing weak asymptotics is developed
Tolkachev E.N.
2017-01-01
The influence of several design and operating parameters of conveyor on the individual components of the stretching tension in the belt of conveyor with suspended belt and distributed drive was analyzed. The analysis of influence a number design and operating parameters on the technical specifications of conveyor with suspended belt and distributed drive was done. Recommendations on the choice of rational parameters were formulated.
Zhan, Hanyu; Voelz, David G.
2016-12-01
The polarimetric bidirectional reflectance distribution function (pBRDF) describes the relationships between incident and scattered Stokes parameters, but the familiar surface-only microfacet pBRDF cannot capture diffuse scattering contributions and depolarization phenomena. We propose a modified pBRDF model with a diffuse scattering component developed from the Kubelka-Munk and Le Hors et al. theories, and apply it in the development of a method to jointly estimate refractive index, slope variance, and diffuse scattering parameters from a series of Stokes parameter measurements of a surface. An application of the model and estimation approach to experimental data published by Priest and Meier shows improved correspondence with measurements of normalized Mueller matrix elements. By converting the Stokes/Mueller calculus formulation of the model to a degree of polarization (DOP) description, the estimation results of the parameters from measured DOP values are found to be consistent with a previous DOP model and results.
International Nuclear Information System (INIS)
Gu Weizu; Lu Jieju; Lu Mingjiang; Chen Tingyang
1988-01-01
A case study of spatial variability of Philip's infiltration parameters was carried out in a small experimental catchment with an area of 0.8 ha by nuclear monitoring methods. Relationships between sorptivity S, parameter A and the average initial soil water content within 0.5 m depth of soil profiles over the catchment have been plotted. A watershed infiltration parameter distribution curve is set up and fitted approximately by f/F=1-(1-S/S M ) n . The parameters of composite infiltration response related to whole catchment are suggested. The author has studied it on an experimental basin by combined method of nuclear technology and micro-geomorphic analysis. The results are satisfactory. (author). 6 refs, 11 figs, 2 tabs
Li, Jiangtao; Zhao, Zheng; Li, Longjie; He, Jiaxin; Li, Chenjie; Wang, Yifeng; Su, Can
2017-09-01
A transmission line transformer has potential advantages for nanosecond pulse generation including excellent frequency response and no leakage inductance. The wave propagation process in a secondary mode line is indispensable due to an obvious inside transient electromagnetic transition in this scenario. The equivalent model of the transmission line transformer is crucial for predicting the output waveform and evaluating the effects of magnetic cores on output performance. However, traditional lumped parameter models are not sufficient for nanosecond pulse generation due to the natural neglect of wave propagations in secondary mode lines based on a lumped parameter assumption. In this paper, a distributed parameter model of transmission line transformer was established to investigate wave propagation in the secondary mode line and its influential factors through theoretical analysis and experimental verification. The wave propagation discontinuity in the secondary mode line induced by magnetic cores is emphasized. Characteristics of the magnetic core under a nanosecond pulse were obtained by experiments. Distribution and formation of the secondary mode current were determined for revealing essential wave propagation processes in secondary mode lines. The output waveform and efficiency were found to be affected dramatically by wave propagation discontinuity in secondary mode lines induced by magnetic cores. The proposed distributed parameter model was proved more suitable for nanosecond pulse generation in aspects of secondary mode current, output efficiency, and output waveform. In depth, comprehension of underlying mechanisms and a broader view of the working principle of the transmission line transformer for nanosecond pulse generation can be obtained through this research.
Directory of Open Access Journals (Sweden)
W. Castaings
2009-04-01
Full Text Available Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised with respect to model inputs.
In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations but didactic application case.
It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run and the singular value decomposition (SVD of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation.
For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers is adopted.
Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.
International Nuclear Information System (INIS)
Gao, Li-Na; Liu, Fu-Hu; Lacey, Roy A.
2016-01-01
Experimental results of the transverse-momentum distributions of φ mesons and Ω hyperons produced in gold-gold (Au-Au) collisions with different centrality intervals, measured by the STAR Collaboration at different energies (7.7, 11.5, 19.6, 27, and 39 GeV) in the beam energy scan (BES) program at the relativistic heavy-ion collider (RHIC), are approximately described by the single Erlang distribution and the two-component Schwinger mechanism. Moreover, the STAR experimental transverse-momentum distributions of negatively charged particles, produced in Au-Au collisions at RHIC BES energies, are approximately described by the two-component Erlang distribution and the single Tsallis statistics. The excitation functions of free parameters are obtained from the fit to the experimental data. A weak softest point in the string tension in Ω hyperon spectra is observed at 7.7 GeV. (orig.)
International Nuclear Information System (INIS)
Pazirandeh, A.; Nasiri, S. H.
2012-01-01
Optimization of the fuel burn up is an important issue in nuclear reactor fuel management and technology. Radial enrichment distribution in the reactor core is a conventional method and axial enrichment is constant along the fuel rod. In this article, the effects of axial enrichment distribution variation on neutronic parameters of PWR core are studied. The axial length of the core is divided into ten sections, considering axial enrichment variation and leaving the existing radial enrichment distribution intact. This study shows that the radial and axial power peaking factors are decreased as compared with the typical conventional core. In addition, the first core lifetime lasts 30 days longer than normal PWR core. Moreover, at the same time boric acid density is 0.2 g/kg at the beginning of the cycle. The flux shape is also flat at the beginning of the cycle for the proposed configuration of the axially enrichment distribution.
Directory of Open Access Journals (Sweden)
Antonova Anastasia O.
2016-01-01
Full Text Available Mathematical model for a polycrystalline specimen and EBSD experiment is proposed. As the measurement parameters, the scanning step and the threshold disorientation angle are considered. To study the impact of the measurement parameters Pole Figures and Orientation Distribution Function of model specimen and corresponding ones, calculated from model EBSD measurements, are compared. The real EBSD experiment was also performed. The results of the model experiment are correlated with such detected in the real EBSD data. The most significant results are formulated in the given work.
Application of the exact distribution pjk in the determination of kinetic parameters in a reactor
International Nuclear Information System (INIS)
Alcala Ruiz, F.
1982-01-01
In this report one distribution of neutron counts obtained by a detector placed in a reactor is studied in order to be used in the determination of reactor kinetic parameters such as β/Λ and reactivities. The parameters accuracy from this new method is compared with the Feynman and Mogilner method, based too in Reactor Neutron Noise Analysis. These three methods have been applied to JEN-2 reactor and the better accuracy and faster collection of experimental data give some interest to the new method which only requires a good footing code. (Author) 68 refs
Energy Technology Data Exchange (ETDEWEB)
McGinn, Christopher F.
2016-12-15
The flow of the quenched energy in imbalanced dijet events has been previously studied by transverse vector sum of charged particles with the CMS detector, namely the missing p{sub T} measurement. The results have led to new theoretical insights to order to explain the wide angle radiation. The missing p{sub T} technique has been improved so that it allows the study of angular distribution of the energy flow with respect to the dijet axis. The measurements are performed using different distance parameters R with the anti-k{sub T} clustering algorithm, which provide information about how the angular distribution of the quenched energy depends on the jet width.
Pescara benchmarks: nonlinear identification
Gandino, E.; Garibaldi, L.; Marchesiello, S.
2011-07-01
Recent nonlinear methods are suitable for identifying large systems with lumped nonlinearities, but in practice most structural nonlinearities are distributed and an ideal nonlinear identification method should cater for them as well. In order to extend the current NSI method to be applied also on realistic large engineering structures, a modal counterpart of the method is proposed in this paper. The modal NSI technique is applied on one of the reinforced concrete beams that have been tested in Pescara, under the project titled "Monitoring and diagnostics of railway bridges by means of the analysis of the dynamic response due to train crossing", financed by Italian Ministry of Research. The beam showed a softening nonlinear behaviour, so that the nonlinearity concerning the first mode is characterized and its force contribution is quantified. Moreover, estimates for the modal parameters are obtained and the model is validated by comparing the measured and the reconstructed output. The identified estimates are also used to accurately predict the behaviour of the same beam, when subject to different initial conditions.
Pescara benchmarks: nonlinear identification
International Nuclear Information System (INIS)
Gandino, E; Garibaldi, L; Marchesiello, S
2011-01-01
Recent nonlinear methods are suitable for identifying large systems with lumped nonlinearities, but in practice most structural nonlinearities are distributed and an ideal nonlinear identification method should cater for them as well. In order to extend the current NSI method to be applied also on realistic large engineering structures, a modal counterpart of the method is proposed in this paper. The modal NSI technique is applied on one of the reinforced concrete beams that have been tested in Pescara, under the project titled M onitoring and diagnostics of railway bridges by means of the analysis of the dynamic response due to train crossing , financed by Italian Ministry of Research. The beam showed a softening nonlinear behaviour, so that the nonlinearity concerning the first mode is characterized and its force contribution is quantified. Moreover, estimates for the modal parameters are obtained and the model is validated by comparing the measured and the reconstructed output. The identified estimates are also used to accurately predict the behaviour of the same beam, when subject to different initial conditions.
Aryan, Homayon; Yearby, Keith; Balikhin, Michael; Agapitov, Oleksiy; Krasnoselskikh, Vladimir; Boynton, Richard
2014-08-01
Energetic electrons within the Earth's radiation belts represent a serious hazard to geostationary satellites. The interactions of electrons with chorus waves play an important role in both the acceleration and loss of radiation belt electrons. The common approach is to present model wave distributions in the inner magnetosphere under different values of geomagnetic activity as expressed by the geomagnetic indices. However, it has been shown that only around 50% of geomagnetic storms increase flux of relativistic electrons at geostationary orbit while 20% causes a decrease and the remaining 30% has relatively no effect. This emphasizes the importance of including solar wind parameters such as bulk velocity (V), density (n), flow pressure (P), and the vertical interplanetary magnetic field component (Bz) that are known to be predominately effective in the control of high energy fluxes at the geostationary orbit. Therefore, in the present study the set of parameters of the wave distributions is expanded to include the solar wind parameters in addition to the geomagnetic activity. The present study examines almost 4 years (1 January 2004 to 29 September 2007) of Spatio-Temporal Analysis of Field Fluctuation data from Double Star TC1 combined with geomagnetic indices and solar wind parameters from OMNI database in order to present a comprehensive model of wave magnetic field intensities for the chorus waves as a function of magnetic local time, L shell (L), magnetic latitude (λm), geomagnetic activity, and solar wind parameters. Generally, the results indicate that the intensity of chorus emission is not only dependent upon geomagnetic activity but also dependent on solar wind parameters with velocity and southward interplanetary magnetic field Bs (Bz < 0), evidently the most influential solar wind parameters. The largest peak chorus intensities in the order of 50 pT are observed during active conditions, high solar wind velocities, low solar wind densities, high
Directory of Open Access Journals (Sweden)
H. C. Winsemius
2008-12-01
Full Text Available In this study, land surface related parameter distributions of a conceptual semi-distributed hydrological model are constrained by employing time series of satellite-based evaporation estimates during the dry season as explanatory information. The approach has been applied to the ungauged Luangwa river basin (150 000 (km^{2} in Zambia. The information contained in these evaporation estimates imposes compliance of the model with the largest outgoing water balance term, evaporation, and a spatially and temporally realistic depletion of soil moisture within the dry season. The model results in turn provide a better understanding of the information density of remotely sensed evaporation. Model parameters to which evaporation is sensitive, have been spatially distributed on the basis of dominant land cover characteristics. Consequently, their values were conditioned by means of Monte-Carlo sampling and evaluation on satellite evaporation estimates. The results show that behavioural parameter sets for model units with similar land cover are indeed clustered. The clustering reveals hydrologically meaningful signatures in the parameter response surface: wetland-dominated areas (also called dambos show optimal parameter ranges that reflect vegetation with a relatively small unsaturated zone (due to the shallow rooting depth of the vegetation which is easily moisture stressed. The forested areas and highlands show parameter ranges that indicate a much deeper root zone which is more drought resistent. Clustering was consequently used to formulate fuzzy membership functions that can be used to constrain parameter realizations in further calibration. Unrealistic parameter ranges, found for instance in the high unsaturated soil zone values in the highlands may indicate either overestimation of satellite-based evaporation or model structural deficiencies. We believe that in these areas, groundwater uptake into the root zone and lateral movement of
International Nuclear Information System (INIS)
Berman, V.G.; Mishurov, Yu.N.
1980-01-01
Gas flow and its density distribution in the Galaxy spiral arm gravitational potential is calculated by means of the nonlinear theory. Line profile of H I emission in 21 cm based on the Galaxy spiral structure models proposed by Lin and Marochnik are constructed for the galactic coordinates 30 deg < or approximately |l| < or approximately 60 deg. It is shown that the conclusion about the possibility of agreement of the Marochnik model with observations made by means of the linear theory is confirmed in the nonlinear theory. In the Marochnik model distributions with R H II regions, CO-clouds, γ-radiation, supernova remnants and so on may also be understood connecting them with variation of gas compression in galactic shock with H radius
Abhinav, S.; Manohar, C. S.
2018-03-01
The problem of combined state and parameter estimation in nonlinear state space models, based on Bayesian filtering methods, is considered. A novel approach, which combines Rao-Blackwellized particle filters for state estimation with Markov chain Monte Carlo (MCMC) simulations for parameter identification, is proposed. In order to ensure successful performance of the MCMC samplers, in situations involving large amount of dynamic measurement data and (or) low measurement noise, the study employs a modified measurement model combined with an importance sampling based correction. The parameters of the process noise covariance matrix are also included as quantities to be identified. The study employs the Rao-Blackwellization step at two stages: one, associated with the state estimation problem in the particle filtering step, and, secondly, in the evaluation of the ratio of likelihoods in the MCMC run. The satisfactory performance of the proposed method is illustrated on three dynamical systems: (a) a computational model of a nonlinear beam-moving oscillator system, (b) a laboratory scale beam traversed by a loaded trolley, and (c) an earthquake shake table study on a bending-torsion coupled nonlinear frame subjected to uniaxial support motion.
Degeling, Koen; Ijzerman, Maarten J.; Koopman, Miriam; Koffijberg, Hendrik
2017-01-01
Background: Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive
Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik
2017-01-01
Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive
Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks
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José Raúl Machado-Fernández
2016-12-01
Full Text Available The main problem faced by naval radars is the elimination of the clutter input which is a distortion signal appearing mixed with target reflections. Recently, the Pareto distribution has been related to sea clutter measurements suggesting that it may provide a better fit than other traditional distributions. The authors propose a new method for estimating the Pareto shape parameter based on artificial neural networks. The solution achieves a precise estimation of the parameter, having a low computational cost, and outperforming the classic method which uses Maximum Likelihood Estimates (MLE. The presented scheme contributes to the development of the NATE detector for Pareto clutter, which uses the knowledge of clutter statistics for improving the stability of the detection, among other applications.
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Hamdy Mohamed Salem
2018-03-01
Full Text Available This paper considers life-testing experiments and how it is effected by stress factors: namely temperature, electricity loads, cycling rate and pressure. A major type of accelerated life tests is a step-stress model that allows the experimenter to increase stress levels more than normal use during the experiment to see the failure items. The test items are assumed to follow Gamma Dual Weibull distribution. Different methods for estimating the parameters are discussed. These include Maximum Likelihood Estimations and Confidence Interval Estimations which is based on asymptotic normality generate narrow intervals to the unknown distribution parameters with high probability. MathCAD (2001 program is used to illustrate the optimal time procedure through numerical examples.
Prediction of the Voltage Quality in an Overhead Transmission Line with Distributed Parameters
Bulyga Leonid L.; Tarasov Evgeniy V.; Ushakov Vasily Ya.; Kharlov Nikolay N.
2015-01-01
The present work is devoted to investigation of an electrical transmission line with allowance for distributed parameters. From the results of voltage measurements at terminals of an actual transmission line, effective values of the voltage are calculated for every line section. Special attention is given to higher harmonics and asymmetry. Spectral composition of the voltage is presented and changes in values of harmonic components are analyzed. The effect of higher harmonics on the equipment...
Prediction of the Voltage Quality in an Overhead Transmission Line with Distributed Parameters
Directory of Open Access Journals (Sweden)
Bulyga Leonid L.
2015-01-01
Full Text Available The present work is devoted to investigation of an electrical transmission line with allowance for distributed parameters. From the results of voltage measurements at terminals of an actual transmission line, effective values of the voltage are calculated for every line section. Special attention is given to higher harmonics and asymmetry. Spectral composition of the voltage is presented and changes in values of harmonic components are analyzed. The effect of higher harmonics on the equipment operation is analyzed.
Degeling, Koen; IJzerman, Maarten J.; Koopman, Miriam; Koffijberg, Hendrik
2017-01-01
Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by ...
Modified distribution parameter for churn-turbulent flows in large diameter channels
International Nuclear Information System (INIS)
Schlegel, J.P.; Macke, C.J.; Hibiki, T.; Ishii, M.
2013-01-01
Highlights: • Void fraction data collected in pipe sizes up to 0.304 m using impedance void meters. • Flow conditions extend to transition between churn-turbulent and annular flow. • Flow regime identification results agree with previous studies. • A new model for the distribution parameter in churn-turbulent flow is proposed. -- Abstract: Two phase flows in large diameter channels are important in a wide range of industrial applications, but especially in analysis of nuclear reactor safety for the prediction of BWR behavior and safety analysis in PWRs. To remedy an inability of current drift-flux models to accurately predict the void fraction in churn-turbulent flows in large diameter pipes, extensive experiments have been performed in pipes with diameters of 0.152 m, 0.203 m and 0.304 m to collect area-averaged void fraction data using electrical impedance void meters. The standard deviation and skewness of the impedance meter signal have been used to characterize the flow regime and confirm previous flow regime transition results. By treating churn-turbulent flow as a transition between cap-bubbly dispersed flow and annular separated flow and using a linear ramp, the distribution parameter has been modified for churn-turbulent flow. The modified distribution parameter has been evaluated through comparison of the void fraction predicted by the drift-flux model and the measured void fraction
Modified distribution parameter for churn-turbulent flows in large diameter channels
Energy Technology Data Exchange (ETDEWEB)
Schlegel, J.P., E-mail: jschlege@purdue.edu; Macke, C.J.; Hibiki, T.; Ishii, M.
2013-10-15
Highlights: • Void fraction data collected in pipe sizes up to 0.304 m using impedance void meters. • Flow conditions extend to transition between churn-turbulent and annular flow. • Flow regime identification results agree with previous studies. • A new model for the distribution parameter in churn-turbulent flow is proposed. -- Abstract: Two phase flows in large diameter channels are important in a wide range of industrial applications, but especially in analysis of nuclear reactor safety for the prediction of BWR behavior and safety analysis in PWRs. To remedy an inability of current drift-flux models to accurately predict the void fraction in churn-turbulent flows in large diameter pipes, extensive experiments have been performed in pipes with diameters of 0.152 m, 0.203 m and 0.304 m to collect area-averaged void fraction data using electrical impedance void meters. The standard deviation and skewness of the impedance meter signal have been used to characterize the flow regime and confirm previous flow regime transition results. By treating churn-turbulent flow as a transition between cap-bubbly dispersed flow and annular separated flow and using a linear ramp, the distribution parameter has been modified for churn-turbulent flow. The modified distribution parameter has been evaluated through comparison of the void fraction predicted by the drift-flux model and the measured void fraction.
International Nuclear Information System (INIS)
Wang, Pan; Lu, Zhenzhou; Ren, Bo; Cheng, Lei
2013-01-01
The output variance is an important measure for the performance of a structural system, and it is always influenced by the distribution parameters of inputs. In order to identify the influential distribution parameters and make it clear that how those distribution parameters influence the output variance, this work presents the derivative based variance sensitivity decomposition according to Sobol′s variance decomposition, and proposes the derivative based main and total sensitivity indices. By transforming the derivatives of various orders variance contributions into the form of expectation via kernel function, the proposed main and total sensitivity indices can be seen as the “by-product” of Sobol′s variance based sensitivity analysis without any additional output evaluation. Since Sobol′s variance based sensitivity indices have been computed efficiently by the sparse grid integration method, this work also employs the sparse grid integration method to compute the derivative based main and total sensitivity indices. Several examples are used to demonstrate the rationality of the proposed sensitivity indices and the accuracy of the applied method
Zuo, S.; Dai, S.; Ren, Y.; Yu, Z.
2017-12-01
Scientifically revealing the spatial heterogeneity and the relationship between the fragmentation of urban landscape and the direct carbon emissions are of great significance to land management and urban planning. In fact, the linear and nonlinear effects among the various factors resulted in the carbon emission spatial map. However, there is lack of the studies on the direct and indirect relations between the carbon emission and the city functional spatial form changes, which could not be reflected by the land use change. The linear strength and direction of the single factor could be calculated through the correlation and Geographically Weighted Regression (GWR) analysis, the nonlinear power of one factor and the interaction power of each two factors could be quantified by the Geodetector analysis. Therefore, we compared the landscape fragmentation metrics of the urban land cover and functional district patches to characterize the landscape form and then revealed the relations between the landscape fragmentation level and the direct the carbon emissions based on the three methods. The results showed that fragmentation decreased and the fragmented patches clustered at the coarser resolution. The direct CO2 emission density and the population density increased when the fragmentation level aggregated. The correlation analysis indicated the weak linear relation between them. The spatial variation of GWR output indicated the fragmentation indicator (MESH) had the positive influence on the carbon emission located in the relatively high emission region, and the negative effects regions accounted for the small part of the area. The Geodetector which explores the nonlinear relation identified the DIVISION and MESH as the most powerful direct factor for the land cover patches, NP and PD for the functional district patches, and the interactions between fragmentation indicator (MESH) and urban sprawl metrics (PUA and DIS) had the greatly increased explanation powers on the
Kawano, N.; Varquez, A. C. G.; Dong, Y.; Kanda, M.
2016-12-01
Numerical model such as Weather Research and Forecasting model coupled with single-layer Urban Canopy Model (WRF-UCM) is one of the powerful tools to investigate urban heat island. Urban parameters such as average building height (Have), plain area index (λp) and frontal area index (λf), are necessary inputs for the model. In general, these parameters are uniformly assumed in WRF-UCM but this leads to unrealistic urban representation. Distributed urban parameters can also be incorporated into WRF-UCM to consider a detail urban effect. The problem is that distributed building information is not readily available for most megacities especially in developing countries. Furthermore, acquiring real building parameters often require huge amount of time and money. In this study, we investigated the potential of using globally available satellite-captured datasets for the estimation of the parameters, Have, λp, and λf. Global datasets comprised of high spatial resolution population dataset (LandScan by Oak Ridge National Laboratory), nighttime lights (NOAA), and vegetation fraction (NASA). True samples of Have, λp, and λf were acquired from actual building footprints from satellite images and 3D building database of Tokyo, New York, Paris, Melbourne, Istanbul, Jakarta and so on. Regression equations were then derived from the block-averaging of spatial pairs of real parameters and global datasets. Results show that two regression curves to estimate Have and λf from the combination of population and nightlight are necessary depending on the city's level of development. An index which can be used to decide which equation to use for a city is the Gross Domestic Product (GDP). On the other hand, λphas less dependence on GDP but indicated a negative relationship to vegetation fraction. Finally, a simplified but precise approximation of urban parameters through readily-available, high-resolution global datasets and our derived regressions can be utilized to estimate a
distributed parameter model of spiral-wound sepralator for treatment of uranyl nitrate effluents
International Nuclear Information System (INIS)
El-Bialy, S.H; Elsherbiny, A.E.
2004-01-01
in this paper, mathematical formulation of spiral-wound sepralator was derived and applied for the treatment of effluent stream which is produced during nuclear fuel processing stage. the concentration of the stream has a value up to 200 ppm . cross-flow characteristic of both feed and permeate streams was taken into account and their mutual effects on the values of system variables were investigated. of course, such a flow pattern leads to a heterogeneous system which leads-in turn-to six partial differential equations, beside a set of algebraic equations. those were solved numerically and the results were used to estimate the average values of both permeate flux and percent solute rejection. then, these were compared with both experimental data in addition to the results of lumped parameter model. the study showed that distributed parameter model gives better results than lumped parameter one compared with experimental data
International Nuclear Information System (INIS)
Mohammadi, Kasra; Alavi, Omid; Mostafaeipour, Ali; Goudarzi, Navid; Jalilvand, Mahdi
2016-01-01
Highlights: • Effectiveness of six numerical methods is evaluated to determine wind power density. • More appropriate method for computing the daily wind power density is estimated. • Four windy stations located in the south part of Alberta, Canada namely is investigated. • The more appropriate parameters estimation method was not identical among all examined stations. - Abstract: In this study, the effectiveness of six numerical methods is evaluated to determine the shape (k) and scale (c) parameters of Weibull distribution function for the purpose of calculating the wind power density. The selected methods are graphical method (GP), empirical method of Justus (EMJ), empirical method of Lysen (EML), energy pattern factor method (EPF), maximum likelihood method (ML) and modified maximum likelihood method (MML). The purpose of this study is to identify the more appropriate method for computing the wind power density in four stations distributed in Alberta province of Canada namely Edmonton City Center Awos, Grande Prairie A, Lethbridge A and Waterton Park Gate. To provide a complete analysis, the evaluations are performed on both daily and monthly scales. The results indicate that the precision of computed wind power density values change when different parameters estimation methods are used to determine the k and c parameters. Four methods of EMJ, EML, EPF and ML present very favorable efficiency while the GP method shows weak ability for all stations. However, it is found that the more effective method is not similar among stations owing to the difference in the wind characteristics.
Kaulakys, B.; Alaburda, M.; Ruseckas, J.
2016-05-01
A well-known fact in the financial markets is the so-called ‘inverse cubic law’ of the cumulative distributions of the long-range memory fluctuations of market indicators such as a number of events of trades, trading volume and the logarithmic price change. We propose the nonlinear stochastic differential equation (SDE) giving both the power-law behavior of the power spectral density and the long-range dependent inverse cubic law of the cumulative distribution. This is achieved using the suggestion that when the market evolves from calm to violent behavior there is a decrease of the delay time of multiplicative feedback of the system in comparison to the driving noise correlation time. This results in a transition from the Itô to the Stratonovich sense of the SDE and yields a long-range memory process.
Zhou, C.; Liu, L.; Lane, J.W.
2001-01-01
A nonlinear tomographic inversion method that uses first-arrival travel-time and amplitude-spectra information from cross-hole radar measurements was developed to simultaneously reconstruct electromagnetic velocity and attenuation distribution in earth materials. Inversion methods were developed to analyze single cross-hole tomography surveys and differential tomography surveys. Assuming the earth behaves as a linear system, the inversion methods do not require estimation of source radiation pattern, receiver coupling, or geometrical spreading. The data analysis and tomographic inversion algorithm were applied to synthetic test data and to cross-hole radar field data provided by the US Geological Survey (USGS). The cross-hole radar field data were acquired at the USGS fractured-rock field research site at Mirror Lake near Thornton, New Hampshire, before and after injection of a saline tracer, to monitor the transport of electrically conductive fluids in the image plane. Results from the synthetic data test demonstrate the algorithm computational efficiency and indicate that the method robustly can reconstruct electromagnetic (EM) wave velocity and attenuation distribution in earth materials. The field test results outline zones of velocity and attenuation anomalies consistent with the finding of previous investigators; however, the tomograms appear to be quite smooth. Further work is needed to effectively find the optimal smoothness criterion in applying the Tikhonov regularization in the nonlinear inversion algorithms for cross-hole radar tomography. ?? 2001 Elsevier Science B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Bizhong Xia
2017-12-01
Full Text Available State of charge (SOC estimation is the core of any battery management system. Most closed-loop SOC estimation algorithms are based on the equivalent circuit model with fixed parameters. However, the parameters of the equivalent circuit model will change as temperature or SOC changes, resulting in reduced SOC estimation accuracy. In this paper, two SOC estimation algorithms with online parameter identification are proposed to solve this problem based on forgetting factor recursive least squares (FFRLS and nonlinear Kalman filter. The parameters of a Thevenin model are constantly updated by FFRLS. The nonlinear Kalman filter is used to perform the recursive operation to estimate SOC. Experiments in variable temperature environments verify the effectiveness of the proposed algorithms. A combination of four driving cycles is loaded on lithium-ion batteries to test the adaptability of the approaches to different working conditions. Under certain conditions, the average error of the SOC estimation dropped from 5.6% to 1.1% after adding the online parameters identification, showing that the estimation accuracy of proposed algorithms is greatly improved. Besides, simulated measurement noise is added to the test data to prove the robustness of the algorithms.
International Nuclear Information System (INIS)
Jiang Haimei; Liu Xinjian; Qiu Lin; Li Fengju
2014-01-01
Based on the meteorological data from weather stations around several domestic nuclear power plants, the statistical results of extreme minimum temperatures, minimum. central pressures of tropical cyclones and some other parameters are calculated using extreme value I distribution function (EV- I), generalized extreme value distribution function (GEV) and generalized Pareto distribution function (GP), respectively. The influence of different distribution functions and parameter solution methods on the statistical results of extreme values is investigated. Results indicate that generalized extreme value function has better applicability than the other two distribution functions in the determination of standard meteorological parameters for nuclear power plants. (authors)
Directory of Open Access Journals (Sweden)
L. Bouchoucha
2018-03-01
Full Text Available In this work, we represent the principle of quantum cryptography (QC that is based on fundamental laws of quantum physics. QC or Quantum Key Distribution (QKD uses various protocols to exchange a secret key between two communicating parties. This research paper focuses and examines the quantum key distribution by using the protocol BB84 in the case of encoding on the single-photon polarization and shows the influence of optical components parameters on the quantum key distribution. We also introduce Quantum Bit Error Rate (QBER to better interpret our results and show its relationship with the intrusion of the eavesdropper called Eve on the optical channel to exploit these vulnerabilities.
International Nuclear Information System (INIS)
Chernov, N.I.; Kurbatov, V.S.; Ososkov, G.A.
1988-01-01
Parameter estimation for multivariate probability distributions is studied in experiments where data are presented as one-dimensional hystograms. For this model a statistics defined as a quadratic form of the observed frequencies which has a limitig x 2 -distribution is proposed. The efficiency of the estimator minimizing the value of that statistics is proved whithin the class of all unibased estimates obtained via minimization of quadratic forms of observed frequencies. The elaborated method was applied to the physical problem of analysis of the secondary pion energy distribution in the isobar model of pion-nucleon interactions with the production of an additional pion. The numerical experiments showed that the accuracy of estimation is twice as much if comparing the conventional methods
International Nuclear Information System (INIS)
Mironov, Yu.V.; Shpanskij, S.V.
1975-01-01
The paper describes PUCHOK-2, a program for thermohydraulic calculation of a channel with a bundle of smooth fuel elements. The pro.gram takes into consideration the non-uniformity of flow parameter distributions over the channel cross-section. The channel cross-section was divided into elementary cells, within which changes in flow parameters (mass velocity, heat- and steam content) were disregarded. The bundle was considered to be a system of parallel interconnected channels. Accounting for equal pressure drops in all the cells, the above model led to a system of non-linear algebraic equations. The system of equations was solved by the method of successive approximations. Theoretical results were compared with experimental data
Dimensionality of heavy metal distribution in waste disposal sites using nonlinear dynamics
International Nuclear Information System (INIS)
Modis, Kostas; Komnitsas, Kostas
2008-01-01
Mapping of heavy metal contamination in mining and waste disposal sites usually relies on geostatistical approaches and linear stochastic dynamics. The present paper aims to identify, using the Grassberger-Procaccia correlation dimension (CD) algorithm, the existence of a nonlinear deterministic and chaotic dynamic behaviour in the spatial pattern of arsenic, manganese and zinc concentration in a Russian coal waste disposal site. The analysis carried out yielded embedding dimension values ranging between 7 and 8 suggesting thus from a chaotic dynamic perspective that arsenic, manganese and zinc concentration in space is a medium dimensional problem for the regionalized scale considered in this study. This alternative nonlinear dynamics approach may complement conventional geostatistical studies and may be also used for the estimation of risk and the subsequent screening and selection of a feasible remediation scheme in wider mining and waste disposal sites. Finally, the synergistic effect of this study may be further elaborated if additional factors including among others presence of hot spots, density and depth of sampling, mineralogy of wastes and sensitivity of analytical techniques are taken into account
Distribution-centric 3-parameter thermodynamic models of partition gas chromatography.
Blumberg, Leonid M
2017-03-31
If both parameters (the entropy, ΔS, and the enthalpy, ΔH) of the classic van't Hoff model of dependence of distribution coefficients (K) of analytes on temperature (T) are treated as the temperature-independent constants then the accuracy of the model is known to be insufficient for the needed accuracy of retention time prediction. A more accurate 3-parameter Clarke-Glew model offers a way to treat ΔS and ΔH as functions, ΔS(T) and ΔH(T), of T. A known T-centric construction of these functions is based on relating them to the reference values (ΔS ref and ΔH ref ) corresponding to a predetermined reference temperature (T ref ). Choosing a single T ref for all analytes in a complex sample or in a large database might lead to practically irrelevant values of ΔS ref and ΔH ref for those analytes that have too small or too large retention factors at T ref . Breaking all analytes in several subsets each with its own T ref leads to discontinuities in the analyte parameters. These problems are avoided in the K-centric modeling where ΔS(T) and ΔS(T) and other analyte parameters are described in relation to their values corresponding to a predetermined reference distribution coefficient (K Ref ) - the same for all analytes. In this report, the mathematics of the K-centric modeling are described and the properties of several types of K-centric parameters are discussed. It has been shown that the earlier introduced characteristic parameters of the analyte-column interaction (the characteristic temperature, T char , and the characteristic thermal constant, θ char ) are a special chromatographically convenient case of the K-centric parameters. Transformations of T-centric parameters into K-centric ones and vice-versa as well as the transformations of one set of K-centric parameters into another set and vice-versa are described. Copyright © 2017 Elsevier B.V. All rights reserved.
Sepehry-Fard, F.; Coulthard, Maurice H.
1995-01-01
The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.
The distribution of waves in the inner magnetosphere as a function of solar wind parameters
Aryan, Homayon; Balikhin, Michael A.; Agapitov, Oleksiy; Krasnoselskikh, Vladimir; Yearby, Keith
Energetic electrons within the Earth’s radiation belts represent a serious hazard to geostationary satellites. The interactions of electrons with chorus waves play an important role in both the acceleration and loss of radiation belt electrons. Studies of the evolution of energetic electron fluxes rely heavily on numerical codes in order to model energy and pitch angle diffusion due to electron interaction with plasma waves in the frame of quasilinear approximation. Application of these codes requires knowledge of statistical wave models to present wave distributions in the magnetosphere. A number of such models are based on CRESS, Cluster, THEMIS and other mission data. These models present wave distributions as a function of L-shell, magnetic local time, magnetic latitude and geomagnetic activity expressed by geomagnetic indices (Kp or Ae). However, it has been shown by G. Reeves and co-authors that only 50% of geomagnetic storms increase flux of relativistic electrons at GEO while 20% cause a decrease. This emphasizes the importance of including solar wind parameters in addition to geomagnetic indices. The present study examines almost four years (01, January, 2004 to 29, September, 2007) of STAFF (Spatio-Temporal Analysis of Field Fluctuation) data from Double Star TC1 combined with geomagnetic indices and solar wind parameters from OMNI database in order to present a comprehensive model of chorus wave intensities as a function of L-shell, magnetic local time, magnetic latitude, geomagnetic indices and solar wind parameters. The results show that chorus emission is not only sub-storm dependent but also dependent upon solar wind parameters with solar wind velocity evidently the most influential solar wind parameter. The largest peak intensities are observed for lower band chorus during active conditions, high solar wind velocity, low density and high pressure.
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R. M. STEVANOVIC
2001-02-01
Full Text Available Cell voltage current density dependences for a model electrochemical cell of fixed geometry were calculated for different electrolyte conductivities, Tafel slopes and cathodic exchange current densities. The ratio between the current density at the part of the cathode nearest to the anode and the one furthest away were taken as a measure for the estimation of the current density distribution. The calculations reveal that increasing the conductivity of the electrolyte, as well as increasing the cathodic Tafel slope should both improve the current density distribution. Also, the distribution should be better under total activation control or total diffusion control rather than at mixed activation-diffusion-Ohmic control of the deposition process. On the contrary, changes in the exchange current density should not affect it. These results, being in agreement with common knowledge about the influence of different parameters on the current distribution in an electrochemical cell, demonstrate that a quick estimation of the current distribution can be performed by a simple comparison of the current density at the point of the cathode closest to anode with that at furthest point.
International Nuclear Information System (INIS)
Nalegaev, S S; Petrov, N V; Bespalov, V G
2014-01-01
A numerical reconstruction of spatial distributions of optical radiation propagating through a volume of nonlinear medium at input and output planes of the medium was demonstrated using a scheme of digital holography. A nonlinear Schrodinger equation with Fourier Split-Step method was used as a tool to propagate wavefront in the volume of the medium. Time dependence of the refractive index change was not taken into account.
Xu, Huijun; Gordon, J James; Siebers, Jeffrey V
2011-02-01
A dosimetric margin (DM) is the margin in a specified direction between a structure and a specified isodose surface, corresponding to a prescription or tolerance dose. The dosimetric margin distribution (DMD) is the distribution of DMs over all directions. Given a geometric uncertainty model, representing inter- or intrafraction setup uncertainties or internal organ motion, the DMD can be used to calculate coverage Q, which is the probability that a realized target or organ-at-risk (OAR) dose metric D, exceeds the corresponding prescription or tolerance dose. Postplanning coverage evaluation quantifies the percentage of uncertainties for which target and OAR structures meet their intended dose constraints. The goal of the present work is to evaluate coverage probabilities for 28 prostate treatment plans to determine DMD sampling parameters that ensure adequate accuracy for postplanning coverage estimates. Normally distributed interfraction setup uncertainties were applied to 28 plans for localized prostate cancer, with prescribed dose of 79.2 Gy and 10 mm clinical target volume to planning target volume (CTV-to-PTV) margins. Using angular or isotropic sampling techniques, dosimetric margins were determined for the CTV, bladder and rectum, assuming shift invariance of the dose distribution. For angular sampling, DMDs were sampled at fixed angular intervals w (e.g., w = 1 degree, 2 degrees, 5 degrees, 10 degrees, 20 degrees). Isotropic samples were uniformly distributed on the unit sphere resulting in variable angular increments, but were calculated for the same number of sampling directions as angular DMDs, and accordingly characterized by the effective angular increment omega eff. In each direction, the DM was calculated by moving the structure in radial steps of size delta (=0.1, 0.2, 0.5, 1 mm) until the specified isodose was crossed. Coverage estimation accuracy deltaQ was quantified as a function of the sampling parameters omega or omega eff and delta. The
Aryan, H.; Yearby, K.; Balikhin, M. A.; Krasnoselskikh, V.; Agapitov, O. V.
2013-12-01
The interaction of gyroresonant wave particles with chorus waves largely determine the dynamics of the Earth's radiation belts that effects the acceleration and loss of radiation belt electrons. The common approach is to present model waves distribution in the inner magnetosphere under different values of geomagnetic activity as expressed by the geomagnetic indices. However it is known that solar wind parameters such as bulk velocity (V) and density (n) are more effective in the control of high energy fluxes at the geostationary orbit. Therefore in the present study the set of parameters of the wave distribution is expanded to include the solar wind parameters in addition to the geomagnetic indices. The present study examines almost four years (01, January, 2004 to 29, September, 2007) of Cluster STAFF-SA, Double Star TC1 and OMNI data in order to present a combined model of wave magnetic field intensities for the chorus waves as a function of magnetic local time (MLT), L-shell (L*), geomagnetic activity, and solar wind velocity and density. Generally, the largest wave intensities are observed during average solar wind velocities (3006cm-3. On the other hand the wave intensity is lower and limited between 06:00 to 18:00 MLT for V700kms-1.
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Tudor DRUGAN
2003-08-01
Full Text Available The aim of the paper was to present the usefulness of the binomial distribution in studying of the contingency tables and the problems of approximation to normality of binomial distribution (the limits, advantages, and disadvantages. The classification of the medical keys parameters reported in medical literature and expressing them using the contingency table units based on their mathematical expressions restrict the discussion of the confidence intervals from 34 parameters to 9 mathematical expressions. The problem of obtaining different information starting with the computed confidence interval for a specified method, information like confidence intervals boundaries, percentages of the experimental errors, the standard deviation of the experimental errors and the deviation relative to significance level was solves through implementation in PHP programming language of original algorithms. The cases of expression, which contain two binomial variables, were separately treated. An original method of computing the confidence interval for the case of two-variable expression was proposed and implemented. The graphical representation of the expression of two binomial variables for which the variation domain of one of the variable depend on the other variable was a real problem because the most of the software used interpolation in graphical representation and the surface maps were quadratic instead of triangular. Based on an original algorithm, a module was implements in PHP in order to represent graphically the triangular surface plots. All the implementation described above was uses in computing the confidence intervals and estimating their performance for binomial distributions sample sizes and variable.
Directory of Open Access Journals (Sweden)
Agnieszka Trębicka
2016-05-01
Full Text Available The object of this study is to present a mathematical model of water-supply network and the analysis of basic parameters of water distribution system with a digital model. The reference area is Kleosin village, municipality Juchnowiec Kościelny in podlaskie province, located at the border with Białystok. The study focused on the significance of every change related to the quality and quantity of water delivered to WDS through modeling the basic parameters of water distribution system in different variants of work in order to specify new, more rational ways of exploitation (decrease in pressure value and to define conditions for development and modernization of the water-supply network, with special analysis of the scheme, in frames of specification of the most dangerous places in the network. The analyzed processes are based on copying and developing the existing state of water distribution sub-system (the WDS with the use of mathematical modeling that includes the newest accessible computer techniques.
Directory of Open Access Journals (Sweden)
Álvaro Gutiérrez
2011-11-01
Full Text Available Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA, previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce.
International Nuclear Information System (INIS)
Banks, David; Birke, Manfred; Flem, Belinda; Reimann, Clemens
2015-01-01
Highlights: • A pan-European survey comprises >60 inorganic parameters in 579 tap water samples. • Compliance with standards for inorganic parameters is good (>99% in EU states). • Around 1% non-compliance is observed for arsenic and 0.2% for uranium. • No sample of water contained nitrate in excess of 45 mg/L. • A weak co-variation in Cu and Pb could indicate derivation from plumbing. - Abstract: 579 tap water samples were collected at the European scale and analysed in a single laboratory for more than 60 parameters. This dataset is evaluated here in terms of the statistical distribution of the analysed parameters and compliance with EU and international drinking water regulations. For most parameters a 99% (or better) degree of compliance was achieved. Among the parameters with the higher rates of non-compliance are: arsenic (1% non-compliance in EU member states, 1.6% when samples from non-EU states are also considered) and sodium (0.6%/1.0%). The decision by the WHO to raise its provisional guideline from 15 μg/L (WHO, 2004) to 30 μg/L (WHO, 2011) has reduced non-compliance for uranium from 1.0% to 0.2%. Despite the fact that tap water (i.e. presumed treated water) was collected, many observations can still be interpreted in terms of hydrogeochemical processes. The dataset demonstrates the potential value of very cost-effective, low-density sampling approaches at a continental (European) scale
International Nuclear Information System (INIS)
Dobrzynski, Ludwik
2000-01-01
The Bayesian analysis of the spherical part of the electron momentum density was carried out with the goal of finding the best estimation of the spherically averaged renormalization parameter, z , quantifying the discontinuity in the electron momentum density distribution in Li metal. Three models parametrizing the electron momentum density were considered and nuisance parameters integrated out. The analysis show that the most likely value of z following from the data of Sakurai et al is in the range of 0.45-0.50, while 0.55 is obtained for the data of Schuelke et al . In the maximum entropy reconstruction of the spherical part of the electron momentum density three different algorithms were used. It is shown that all of them produce essentially the same results. The paper shows that the accurate Compton scattering experiments are capable of bringing information on this very important Fermiological aspect of the electron gas in a metal. (author)
Effect of thermohydraulic parameter on the flux distribution and the effective multiplication factor
International Nuclear Information System (INIS)
Mello, J.C.; Valladares, G.L.
1990-01-01
The influence of two thermohydraulics parameters; the coolant flow velocity along the reactor channels and the increase of the average water temperature through the core, on the thermal flux distribution and on the effective multiplication factor, was studied in a radioisotopes production reactor. The results show that, for a fixed values of the thermohydraulics parameters reffered above, there are limits for the reactor core volume reduction for each value of the V sub(mod)/V sub(comb) ratio. These thermohydraulics conditions determine the higher termal flux value in the flux-trap and the lower value of the reactor effective multiplication factor. It is also show that there is a V sub(mod)/V sub(comb) ratio value that correspond to the higher value of the lower effective multiplication factor. These results was interpreted and comment using fundamentals concepts and relations of reactor physics. (author)
Reliability-based sensitivity of mechanical components with arbitrary distribution parameters
International Nuclear Information System (INIS)
Zhang, Yi Min; Yang, Zhou; Wen, Bang Chun; He, Xiang Dong; Liu, Qiaoling
2010-01-01
This paper presents a reliability-based sensitivity method for mechanical components with arbitrary distribution parameters. Techniques from the perturbation method, the Edgeworth series, the reliability-based design theory, and the sensitivity analysis approach were employed directly to calculate the reliability-based sensitivity of mechanical components on the condition that the first four moments of the original random variables are known. The reliability-based sensitivity information of the mechanical components can be accurately and quickly obtained using a practical computer program. The effects of the design parameters on the reliability of mechanical components were studied. The method presented in this paper provides the theoretic basis for the reliability-based design of mechanical components
Miao, Changyun; Shi, Boya; Li, Hongqiang
2008-12-01
A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.
Simplified distributed parameters BWR dynamic model for transient and stability analysis
International Nuclear Information System (INIS)
Espinosa-Paredes, Gilberto; Nunez-Carrera, Alejandro; Vazquez-Rodriguez, Alejandro
2006-01-01
This paper describes a simplified model to perform transient and linear stability analysis for a typical boiling water reactor (BWR). The simplified transient model was based in lumped and distributed parameters approximations, which includes vessel dome and the downcomer, recirculation loops, neutron process, fuel pin temperature distribution, lower and upper plenums reactor core and pressure and level controls. The stability was determined by studying the linearized versions of the equations representing the BWR system in the frequency domain. Numerical examples are used to illustrate the wide application of the simplified BWR model. We concluded that this simplified model describes properly the dynamic of a BWR and can be used for safety analysis or as a first approach in the design of an advanced BWR
Multiple-parameter bifurcation analysis in a Kuramoto model with time delay and distributed shear
Niu, Ben; Zhang, Jiaming; Wei, Junjie
2018-05-01
In this paper, time delay effect and distributed shear are considered in the Kuramoto model. On the Ott-Antonsen's manifold, through analyzing the associated characteristic equation of the reduced functional differential equation, the stability boundary of the incoherent state is derived in multiple-parameter space. Moreover, very rich dynamical behavior such as stability switches inducing synchronization switches can occur in this equation. With the loss of stability, Hopf bifurcating coherent states arise, and the criticality of Hopf bifurcations is determined by applying the normal form theory and the center manifold theorem. On one hand, theoretical analysis indicates that the width of shear distribution and time delay can both eliminate the synchronization then lead the Kuramoto model to incoherence. On the other, time delay can induce several coexisting coherent states. Finally, some numerical simulations are given to support the obtained results where several bifurcation diagrams are drawn, and the effect of time delay and shear is discussed.
Mu, Wenying; Cui, Baotong; Li, Wen; Jiang, Zhengxian
2014-07-01
This paper proposes a scheme for non-collocated moving actuating and sensing devices which is unitized for improving performance in distributed parameter systems. By Lyapunov stability theorem, each moving actuator/sensor agent velocity is obtained. To enhance state estimation of a spatially distributes process, two kinds of filters with consensus terms which penalize the disagreement of the estimates are considered. Both filters can result in the well-posedness of the collective dynamics of state errors and can converge to the plant state. Numerical simulations demonstrate that the effectiveness of such a moving actuator-sensor network in enhancing system performance and the consensus filters converge faster to the plant state when consensus terms are included. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Tolkachev E.N.
2017-03-01
Full Text Available The influence of several design and operating parameters of conveyor on the individual components of the stretching tension in the belt of conveyor with suspended belt and distributed drive was analyzed. The analysis of influence a number design and operating parameters on the technical specifications of conveyor with suspended belt and distributed drive was done. Recommendations on the choice of rational parameters were formulated.
Factorization and the synthesis of optimal feedback gains for distributed parameter systems
Milman, Mark H.; Scheid, Robert E.
1990-01-01
An approach based on Volterra factorization leads to a new methodology for the analysis and synthesis of the optimal feedback gain in the finite-time linear quadratic control problem for distributed parameter systems. The approach circumvents the need for solving and analyzing Riccati equations and provides a more transparent connection between the system dynamics and the optimal gain. The general results are further extended and specialized for the case where the underlying state is characterized by autonomous differential-delay dynamics. Numerical examples are given to illustrate the second-order convergence rate that is derived for an approximation scheme for the optimal feedback gain in the differential-delay problem.
Zhang, Ke; Jiang, Bin; Shi, Peng
2017-02-01
In this paper, a novel adjustable parameter (AP)-based distributed fault estimation observer (DFEO) is proposed for multiagent systems (MASs) with the directed communication topology. First, a relative output estimation error is defined based on the communication topology of MASs. Then a DFEO with AP is constructed with the purpose of improving the accuracy of fault estimation. Based on H ∞ and H 2 with pole placement, multiconstrained design is given to calculate the gain of DFEO. Finally, simulation results are presented to illustrate the feasibility and effectiveness of the proposed DFEO design with AP.
OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE.
Xie, Xianchao; Kou, S C; Brown, Lawrence
2016-03-01
This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semi-parametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results.
Directory of Open Access Journals (Sweden)
Lagerev A.V.
2016-09-01
Full Text Available Using the basic design of the conveyor with suspended belt and distributed drive, a series of numerical calculations was performed. As a result, the influence of friction and mass-dimensional design parameters of suspensions on the main technical parameters of the conveyor was established. Recommendations on the choice of rational parameters were formulated.
Wang, C.; Rubin, Y.
2014-12-01
Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi
DEFF Research Database (Denmark)
Han, Renke; Meng, Lexuan; Guerrero, Josep M.
2018-01-01
combining the state-dependent tolerance with a nonnegative offset. In order to design the event-triggered principle and guarantee the global stability, a generalized dc microgrid model is proposed and proven to be positive definite, based on which Lyapunov-based approach is applied. Furthermore, considering......A distributed nonlinear controller is presented to achieve both accurate current-sharing and voltage regulation simultaneously in dc microgrids considering different line impedances’ effects among converters. Then, an improved event-triggered principle for the controller is introduced through...... for precise real-time information transmission, without sacrificing system performance. Experimental results obtained from a dc microgrid setup show the robustness of the new proposal under normal, communication failure, communication delay and plug-and-play operation conditions. Finally, communication...
Lee, Jin-Yong; Cheon, Jeong-Yong; Lee, Kang-Kun; Lee, Seok-Young; Lee, Min-Hyo
2001-07-01
The distributions of hydrocarbon contaminants and hydrogeochemical parameters were investigated in a shallow sand aquifer highly contaminated with petroleum hydrocarbons leaked from solvent storage tanks. For these purposes, a variety of field investigations and studies were performed, which included installation of over 100 groundwater monitoring wells and piezometers at various depths, soil logging and analyses during well and piezometer installation, chemical analysis of groundwater, pump tests, and slug tests. Continuous water level monitoring at three selected wells using automatic data-logger and manual measuring at other wells were also conducted. Based on analyses of the various investigations and tests, a number of factors were identified to explain the distribution of the hydrocarbon contaminants and hydrogeochemical parameters. These factors include indigenous biodegradation, hydrostratigraphy, preliminary pump-and-treat remedy, recharge by rainfall, and subsequent water level fluctuation. The permeable sandy layer, in which the mean water table elevation is maintained, provided a dominant pathway for contaminant transport. The preliminary pump-and-treat action accelerated the movement of the hydrocarbon contaminants and affected the redox evolution pattern. Seasonal recharge by rain, together with indigenous biodegradation, played an important role in the natural attenuation of the petroleum hydrocarbons via mixing/dilution and biodegradation. The water level fluctuations redistributed the hydrocarbon contaminants by partitioning them into the soil and groundwater. The identified factors are not independent but closely inter-correlated.
Zhang, Jingdong; Zhu, Tao; Zhou, Huan; Huang, Shihong; Liu, Min; Huang, Wei
2016-11-28
We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.
Chen, Chung-De
2018-04-01
In this paper, a distributed parameter electromechanical model for bimorph piezoelectric energy harvesters based on the refined zigzag theory (RZT) is developed. In this model, the zigzag function is incorporated into the axial displacement, and the zigzag distribution of the displacement between the adjacent layers of the bimorph structure can be considered. The governing equations, including three equations of motions and one equation of circuit, are derived using Hamilton’s principle. The natural frequency, its corresponding modal function and the steady state response of the base excitation motion are given in exact forms. The presented results are benchmarked with the finite element method and two beam theories, the first-order shear deformation theory and the classical beam theory. Comparing examples shows that the RZT provides predictions of output voltage and generated power at high accuracy, especially for the case of a soft middle layer. Variation of the parameters, such as the beam thickness, excitation frequencies and the external electrical loads, is investigated and its effects on the performance of the energy harvesters are studied by using the RZT developed in this paper. Based on this refined theory, analysts and engineers can capture more details on the electromechanical behavior of piezoelectric harvesters.
Non-linear properties of R-R distributions as a measure of heart rate variability
International Nuclear Information System (INIS)
Irurzun, I.M.; Bergero, P.; Cordero, M.C.; Defeo, M.M.; Vicente, J.L.; Mola, E.E.
2003-01-01
We analyze the dynamic quality of the R-R interbeat intervals of electrocardiographic signals from healthy people and from patients with premature ventricular contractions (PVCs) by applying different measure algorithms to standardised public domain data sets of heart rate variability. Our aim is to assess the utility of these algorithms for the above mentioned purposes. Long and short time series, 24 and 0.50 h respectively, of interbeat intervals of healthy and PVC subjects were compared with the aim of developing a fast method to investigate their temporal organization. Two different methods were used: power spectral analysis and the integral correlation method. Power spectral analysis has proven to be a powerful tool for detecting long-range correlations. If it is applied in a short time series, power spectra of healthy and PVC subjects show a similar behavior, which disqualifies power spectral analysis as a fast method to distinguish healthy from PVC subjects. The integral correlation method allows us to study the fractal properties of interbeat intervals of electrocardiographic signals. The cardiac activity of healthy and PVC people stems from dynamics of chaotic nature characterized by correlation dimensions d f equal to 3.40±0.50 and 5.00±0.80 for healthy and PVC subjects respectively. The methodology presented in this article bridges the gap between theoretical and experimental studies of non-linear phenomena. From our results we conclude that the minimum number of coupled differential equations to describe cardiac activity must be six and seven for healthy and PVC individuals respectively. From the present analysis we conclude that the correlation integral method is particularly suitable, in comparison with the power spectral analysis, for the early detection of arrhythmias on short time (0.5 h) series
International Nuclear Information System (INIS)
Drozdowicz, K.
1999-01-01
Macroscopic parameters for a description of the thermal neutron transport in finite volumes are considered. A very good correspondence between the theoretical and experimental parameters of hydrogenous media is attained. Thermal neutrons in the medium possess an energy distribution, which is dependent on the size (characterized by the geometric buckling) and on the neutron transport properties of the medium. In a hydrogenous material the thermal neutron transport is dominated by the scattering cross section which is strongly dependent on energy. A monoenergetic treatment of the thermal neutron group (admissible for other materials) leads in this case to a discrepancy between theoretical and experimental results. In the present paper the theoretical definitions of the pulsed thermal neutron parameters (the absorption rate, the diffusion coefficient, and the diffusion cooling coefficient) are based on Nelkin's analysis of the decay of a neutron pulse. Problems of the experimental determination of these parameters for a hydrogenous medium are discussed. A theoretical calculation of the pulsed parameters requires knowledge of the scattering kernel. For thermal neutrons it is individual for each hydrogenous material because neutron scattering on hydrogen nuclei bound in a molecule is affected by the molecular dynamics (characterized with internal energy modes which are comparable to the incident neutron energy). Granada's synthetic model for slow-neutron scattering is used. The complete up-dated formalism of calculation of the energy transfer scattering kernel after this model is presented in the paper. An influence of some minor variants within the model on the calculated differential and integral neutron parameters is shown. The theoretical energy-dependent scattering cross section (of Plexiglas) is compared to experimental results. A particular attention is paid to the calculation of the diffusion cooling coefficient. A solution of an equation, which determines the
Zhou, H.; Liu, W.; Ning, T.
2017-12-01
Land surface actual evapotranspiration plays a key role in the global water and energy cycles. Accurate estimation of evapotranspiration is crucial for understanding the interactions between the land surface and the atmosphere, as well as for managing water resources. The nonlinear advection-aridity approach was formulated by Brutsaert to estimate actual evapotranspiration in 2015. Subsequently, this approach has been verified, applied and developed by many scholars. The estimation, impact factors and correlation analysis of the parameter alpha (αe) of this approach has become important aspects of the research. According to the principle of this approach, the potential evapotranspiration (ETpo) (taking αe as 1) and the apparent potential evapotranspiration (ETpm) were calculated using the meteorological data of 123 sites of the Loess Plateau and its surrounding areas. Then the mean spatial values of precipitation (P), ETpm and ETpo for 13 catchments were obtained by a CoKriging interpolation algorithm. Based on the runoff data of the 13 catchments, actual evapotranspiration was calculated using the catchment water balance equation at the hydrological year scale (May to April of the following year) by ignoring the change of catchment water storage. Thus, the parameter was estimated, and its relationships with P, ETpm and aridity index (ETpm/P) were further analyzed. The results showed that the general range of annual parameter value was 0.385-1.085, with an average value of 0.751 and a standard deviation of 0.113. The mean annual parameter αe value showed different spatial characteristics, with lower values in northern and higher values in southern. The annual scale parameter linearly related with annual P (R2=0.89) and ETpm (R2=0.49), while it exhibited a power function relationship with the aridity index (R2=0.83). Considering the ETpm is a variable in the nonlinear advection-aridity approach in which its effect has been incorporated, the relationship of
International Nuclear Information System (INIS)
Zheng, Lixing; Deng, Jianqiang
2017-01-01
Highlights: • The ejector distributed-parameter model is developed to study ejector efficiencies. • Feasible component and total efficiency correlations of ejector are established. • New efficiency correlations are applied to obtain dynamic characteristics of EERC. • More suitable fixed efficiency value can be determined by the proposed correlations. - Abstract: In this study we combine the experimental measurement data and the theoretical model of ejector to determine CO 2 ejector component efficiencies including the motive nozzle, suction chamber, mixing section, diffuser as well as the total ejector efficiency. The ejector is modeled utilizing the distributed-parameter method, and the flow passage is divided into a number of elements and the governing equations are formulated based on the differential equation of mass, momentum and energy conservation. The efficiencies of ejector are investigated under different ejector geometric parameters and operational conditions, and the corresponding empirical correlations are established. Moreover, the correlations are incorporated into a transient model of transcritical CO 2 ejector expansion refrigeration cycle (EERC) and the dynamic simulations is performed based on variable component efficiencies and fixed values. The motive nozzle, suction chamber, mixing section and diffuser efficiencies vary from 0.74 to 0.89, 0.86 to 0.96, 0.73 to 0.9 and 0.75 to 0.95 under the studied conditions, respectively. The response diversities of suction flow pressure and discharge pressure are obvious between the variable efficiencies and fixed efficiencies referring to the previous studies, while when the fixed value is determined by the presented correlations, their response differences are basically the same.
Directory of Open Access Journals (Sweden)
Pradeep K. Goyal
2011-09-01
Full Text Available This paper presents a study conducted on the probabilistic distribution of key cyclone parameters and the cyclonic wind speed by analyzing the cyclone track records obtained from India meteorological department for east coast region of India. The dataset of historical landfalling storm tracks in India from 1975–2007 with latitude /longitude and landfall locations are used to map the cyclone tracks in a region of study. The statistical tests were performed to find a best fit distribution to the track data for each cyclone parameter. These parameters include central pressure difference, the radius of maximum wind speed, the translation velocity, track angle with site and are used to generate digital simulated cyclones using wind field simulation techniques. For this, different sets of values for all the cyclone key parameters are generated randomly from their probability distributions. Using these simulated values of the cyclone key parameters, the distribution of wind velocity at a particular site is obtained. The same distribution of wind velocity at the site is also obtained from actual track records and using the distributions of the cyclone key parameters as published in the literature. The simulated distribution is compared with the wind speed distributions obtained from actual track records. The findings are useful in cyclone disaster mitigation.
Guasp, J.; Pastor, I.; Álvarez-Estrada, R. F.; Castejón, F.
2015-02-01
Analytical results obtained recently of the ab-initio classical incoherent Thomson Scattering (TS) spectrum from a single-electron (Alvarez-Estrada et al 2012 Phys. Plasmas 19 062302) have been numerically implemented in a paralelized code to efficiently compute the TS emission from a given electron distribution function, irrespective of its characteristics and/or the intensity of the incoming radiation. These analytical results display certain differences, when compared with other authors, in the general case of incoming linearly and circularly polarized radiation and electrons with arbitrary initial directions. We regard such discrepancies and the ubiquitous interest in TS as motivations for this work. Here, we implement some analytical advances (like generalized Bessel functions for incoming linearly polarized radiation) in TS. The bulk of this work reports on the efficient computation of TS spectra (based upon our analytical approach), for an electron population having an essentially arbitrary distribution function and for both incoming linearly and circularly polarized radiation. A detailed comparison between the present approach and a previous Monte Carlo one (Pastor et al 2011 Nuclear Fusion 51 043011), dealing with the ab-initio computation of TS spectra, is reported. Both approaches are shown to fully agree with each other. As key computational improvements, the analytical technique yields a × 30 to × 100 gain in computation time and is a very flexible tool to compute the scattered spectrum and eventually the scattered electromagnetic fields in the time domain. The latter are computed explicitly here for the first time, as far as we know. Scaling laws for the power integrated over frequency versus initial kinetic energy are studied for the case of isotropic and monoenergetic electron distribution functions and their potential application as diagnostic tools for high-energy populations is briefly discussed. Finally, we discuss the application of these
Neoclassical transport including collisional nonlinearity.
Candy, J; Belli, E A
2011-06-10
In the standard δf theory of neoclassical transport, the zeroth-order (Maxwellian) solution is obtained analytically via the solution of a nonlinear equation. The first-order correction δf is subsequently computed as the solution of a linear, inhomogeneous equation that includes the linearized Fokker-Planck collision operator. This equation admits analytic solutions only in extreme asymptotic limits (banana, plateau, Pfirsch-Schlüter), and so must be solved numerically for realistic plasma parameters. Recently, numerical codes have appeared which attempt to compute the total distribution f more accurately than in the standard ordering by retaining some nonlinear terms related to finite-orbit width, while simultaneously reusing some form of the linearized collision operator. In this work we show that higher-order corrections to the distribution function may be unphysical if collisional nonlinearities are ignored.
Ma, Lifeng; Wang, Zidong; Lam, Hak-Keung; Kyriakoulis, Nikos
2017-11-01
In this paper, the distributed set-membership filtering problem is investigated for a class of discrete time-varying system with an event-based communication mechanism over sensor networks. The system under consideration is subject to sector-bounded nonlinearity, unknown but bounded noises and sensor saturations. Each intelligent sensing node transmits the data to its neighbors only when certain triggering condition is violated. By means of a set of recursive matrix inequalities, sufficient conditions are derived for the existence of the desired distributed event-based filter which is capable of confining the system state in certain ellipsoidal regions centered at the estimates. Within the established theoretical framework, two additional optimization problems are formulated: one is to seek the minimal ellipsoids (in the sense of matrix trace) for the best filtering performance, and the other is to maximize the triggering threshold so as to reduce the triggering frequency with satisfactory filtering performance. A numerically attractive chaos algorithm is employed to solve the optimization problems. Finally, an illustrative example is presented to demonstrate the effectiveness and applicability of the proposed algorithm.
Demekhov, A. G.
2017-03-01
By using numerical simulations we generalize certain relationships between the parameters of quasimonochromatic whistler-mode waves generated at the linear and nonlinear stages of the cyclotron instability in the backward-wave oscillator regime. One of these relationships is between the wave amplitude at the nonlinear stage and the linear growth rate of the cyclotron instability. It was obtained analytically by V.Yu.Trakhtengerts (1984) for a uniform medium under the assumption of constant frequency and amplitude of the generated wave. We show that a similar relationship also holds for the signals generated in a nonuniform magnetic field and having a discrete structure in the form of short wave packets (elements) with fast frequency drift inside each element. We also generalize the formula for the linear growth rate of absolute cyclotron instability in a nonuniform medium and analyze the relationship between the frequency drift rate in the discrete elements and the wave amplitude. These relationships are important for analyzing the links between the parameters of chorus emissions in the Earth's and planetary magnetospheres and the characteristics of the energetic charged particles generating these signals.
National Aeronautics and Space Administration — The overall goal of the project is to develop reliable reduced order modeling technologies to automatically generate parameter-varying (PV), aeroservoelastic (ASE)...
Neophytou, Andreas M; Picciotto, Sally; Brown, Daniel M; Gallagher, Lisa E; Checkoway, Harvey; Eisen, Ellen A; Costello, Sadie
2018-02-13
Prolonged exposures can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant. Summary measures such as cumulative exposure or average intensity of exposure may not fully capture these relationships. We applied penalized and unpenalized distributed lag non-linear models (DLNMs) with flexible exposure-response and lag-response functions in order to examine the association between crystalline silica exposure and mortality from lung cancer and non-malignant respiratory disease in a cohort study of 2,342 California diatomaceous earth workers, followed 1942-2011. We also assessed associations using simple measures of cumulative exposure assuming linear exposure-response and constant lag-response. Measures of association from DLNMs were generally higher than from simpler models. Rate ratios from penalized DLNMs corresponding to average daily exposures of 0.4 mg/m3 during lag years 31-50 prior to the age of observed cases were 1.47 (95% confidence interval (CI) 0.92, 2.35) for lung cancer and 1.80 (95% CI: 1.14, 2.85) for non-malignant respiratory disease. Rate ratios from the simpler models for the same exposure scenario were 1.15 (95% CI: 0.89-1.48) and 1.23 (95% CI: 1.03-1.46) respectively. Longitudinal cohort studies of prolonged exposures and chronic health outcomes should explore methods allowing for flexibility and non-linearities in the exposure-lag-response. © The Author(s) 2018. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.
Parallel computation for distributed parameter system-from vector processors to Adena computer
Energy Technology Data Exchange (ETDEWEB)
Nogi, T
1983-04-01
Research on advanced parallel hardware and software architectures for very high-speed computation deserves and needs more support and attention to fulfil its promise. Novel architectures for parallel processing are being made ready. Architectures for parallel processing can be roughly divided into two groups. One is a vector processor in which a single central processing unit involves multiple vector-arithmetic registers. The other is a processor array in which slave processors are connected to a host processor to perform parallel computation. In this review, the concept and data structure of the Adena (alternating-direction edition nexus array) architecture, which is conformable to distributed-parameter simulation algorithms, are described. 5 references.
Study on spatial distribution of plasma parameters in a magnetized inductively coupled plasma
Energy Technology Data Exchange (ETDEWEB)
Cheong, Hee-Woon; Lee, Woohyun; Kim, Ji-Won; Whang, Ki-Woong, E-mail: kwhang@snu.ac.kr [Plasma Laboratory, Inter-University Semiconductor Research Center, Department of Electrical and Computer Engineering, Seoul National University, Seoul 151-742 (Korea, Republic of); Kim, Hyuk [Samsung Electronics Co., Banwol-dong, Hwaseong 445-701 (Korea, Republic of); Park, Wanjae [Tokyo Electron Miyagi Ltd., Taiwa-cho, Kurokawa-gun, Miyagi 981-3629 (Japan)
2015-07-15
Spatial distributions of various plasma parameters such as plasma density, electron temperature, and radical density in an inductively coupled plasma (ICP) and a magnetized inductively coupled plasma (M-ICP) were investigated and compared. Electron temperature in between the rf window and the substrate holder of M-ICP was higher than that of ICP, whereas the one just above the substrate holder of M-ICP was similar to that of ICP when a weak (<8 G) magnetic field was employed. As a result, radical densities in M-ICP were higher than those in ICP and the etch rate of oxide in M-ICP was faster than that in ICP without severe electron charging in 90 nm high aspect ratio contact hole etch.
Retrieval of cloud droplet size distribution parameters from polarized reflectance measurements
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M. Alexandrov
2011-09-01
Full Text Available We present an algorithm for retrieval of cloud droplet size distribution parameters (effective radius and variance from the Research Scanning Polarimeter (RSP measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS, which is due to be launched as part of the NASA Glory Project. This instrument measures both polarized and total reflectances in 9 spectral channels with center wavelengths ranging from 410 to 2250 nm. For cloud droplet size retrievals we utilize the polarized reflectances in the scattering angle range between 140 and 170 degrees where they exhibit rainbow. The shape of the rainbow is determined mainly by single-scattering properties of the cloud particles, that simplifies the inversions and reduces retrieval uncertainties. The retrieval algorithm was tested using realistically simulated cloud radiation fields. Our retrievals of cloud droplet sizes from actual RSP measurements made during two recent field campaigns were compared with the correlative in situ observations.
Technology of solving multi-objective problems of control of systems with distributed parameters
Rapoport, E. Ya.; Pleshivtseva, Yu. E.
2017-07-01
A constructive technology of multi-objective optimization of control of distributed parameter plants is proposed. The technology is based on a single-criterion version in the form of the minimax convolution of normalized performance criteria. The approach under development is based on the transition to an equivalent form of the variational problem with constraints, with the problem solution being a priori Pareto-effective. Further procedures of preliminary parameterization of control actions and subsequent reduction to a special problem of semi-infinite programming make it possible to find the sought extremals with the use of their Chebyshev properties and fundamental laws of the subject domain. An example of multi-objective optimization of operation modes of an engineering thermophysics object is presented, which is of independent interest.
Optimal allocation of sensors for state estimation of distributed parameter systems
International Nuclear Information System (INIS)
Sunahara, Yoshifumi; Ohsumi, Akira; Mogami, Yoshio.
1978-01-01
The purpose of this paper is to present a method for finding the optimal allocation of sensors for state estimation of linear distributed parameter systems. This method is based on the criterion that the error covariance associated with the state estimate becomes minimal with respect to the allocation of the sensors. A theorem is established, giving the sufficient condition for optimizing the allocation of sensors to make minimal the error covariance approximated by a modal expansion. The remainder of this paper is devoted to illustrate important phases of the general theory of the optimal measurement allocation problem. To do this, several examples are demonstrated, including extensive discussions on the mutual relation between the optimal allocation and the dynamics of sensors. (author)
Bandyopadhyay, Saptarshi
guidance algorithms using results from numerical simulations and closed-loop hardware experiments on multiple quadrotors. In the second part of this dissertation, we present two novel discrete-time algorithms for distributed estimation, which track a single target using a network of heterogeneous sensing agents. The Distributed Bayesian Filtering (DBF) algorithm, the sensing agents combine their normalized likelihood functions using the logarithmic opinion pool and the discrete-time dynamic average consensus algorithm. Each agent's estimated likelihood function converges to an error ball centered on the joint likelihood function of the centralized multi-sensor Bayesian filtering algorithm. Using a new proof technique, the convergence, stability, and robustness properties of the DBF algorithm are rigorously characterized. The explicit bounds on the time step of the robust DBF algorithm are shown to depend on the time-scale of the target dynamics. Furthermore, the DBF algorithm for linear-Gaussian models can be cast into a modified form of the Kalman information filter. In the Bayesian Consensus Filtering (BCF) algorithm, the agents combine their estimated posterior pdfs multiple times within each time step using the logarithmic opinion pool scheme. Thus, each agent's consensual pdf minimizes the sum of Kullback-Leibler divergences with the local posterior pdfs. The performance and robust properties of these algorithms are validated using numerical simulations. In the third part of this dissertation, we present an attitude control strategy and a new nonlinear tracking controller for a spacecraft carrying a large object, such as an asteroid or a boulder. If the captured object is larger or comparable in size to the spacecraft and has significant modeling uncertainties, conventional nonlinear control laws that use exact feed-forward cancellation are not suitable because they exhibit a large resultant disturbance torque. The proposed nonlinear tracking control law guarantees
International Nuclear Information System (INIS)
Zeng, Hongtao; Lan, Tian; Chen, Qiming
2016-01-01
Two lifetime distributions derived from Perks' mortality rate function, one with 4 parameters and the other with 5 parameters, for the modeling of bathtub-shaped failure rates are proposed in this paper. The Perks' mortality/failure rate functions have historically been used for human life modeling in life insurance industry. Although this distribution is no longer used in insurance industry, considering many nice and some unique features of this function, it is necessary to revisit it and introduce it to the reliability community. The parameters of the distributions can control the scale, shape, and location of the PDF. The 4-parameter distribution can be used to model the bathtub failure rate. This model is applied to three previously published groups of lifetime data. This study shows they fit very well. The 5-parameter version can potentially model constant hazard rates of the later life of some devices in addition to the good features of 4-parameter version. Both the 4 and 5-parameter versions have closed form PDF and CDF. The truncated distributions of both versions stay within the original distribution family with simple parameter transformation. This nice feature is normally considered to be only possessed by the simple exponential distribution - Highlights: • Two new distributions are proposed to model bathtub shaped hazard rate. • Derive the close-form PDF, CDF and feature of scalability and truncatability. • Perks4 is verified to be good to model common bathtub shapes through comparison. • Perks5 has the potential to model the stabilization of hazard rate at later life.
Parameter study of temperature distribution in a work-piece during dry hyperbaric GTA-welding
International Nuclear Information System (INIS)
Fulfs, H.
1989-01-01
In a sensitivity study the influence of initial and boundary welding parameters upon the spatial and temporal temperature distribution in a work-piece during dry hyperbaric GTA-welding is investigated. It will be shown that at constant arc current a variation of pressure (1-60 bar), arc length (3-10 mm), welding speed (1-2.5 mm/s) or the initial temperature (20-200deg C) of the work-piece to some extend significantly influences the size of melt and heat affected zone as well as the maximum temperature and cooling behaviour of the work-piece; compared to this no mentionable effects of shielding gas temperature (20-300deg C) or flow rate (10-500 dm N 3 /min) on the thermal condition of the work-piece can be recognized. The discovered relationships have been approximated by simple correlations, which can be used for parameter optimization and process control. (orig.) With 33 figs., 4 tabs [de
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D. N. Popov
2015-01-01
verification results of the mathematical model of the hydraulic system in the space-distributed parameters.
Yue, Honghao; Lu, Yifan; Deng, Zongquan; Tzou, Hornsen
2018-03-01
Paraboloidal membrane shells of revolution are commonly used as key components for advanced aerospace structures and aviation mechanical systems. Due to their high flexibility and low damping property, active vibration control is of significant importance for these in-orbit membrane structures. To explore the dynamic control behavior of space flexible paraboloidal membrane shells, precision distributed actuation and control effectiveness of free-floating paraboloidal membrane shells with piezoelectric actuators are investigated. Governing equations of the shell structronic system are presented first. Then, distributed control forces and control actions are formulated. A transverse mode shape function of the paraboloidal shell based on the membrane approximation theory and specified boundary condition is assumed in the modal control force analysis. The actuator induced modal control forces on the paraboloidal shell are derived. The expressions of microscopic local modal control forces are obtained by shrinking the actuator area into infinitesimal and the four control components are investigated respectively to predict the spatial microscopic actuation behavior. Geometric parameter (height-radius ratio and shell thickness) effects on the modal actuation behavior are explored when evaluating the micro-control efficiency. Four different cases are discussed and the results reveal the fact that shallow (e.g., antennas/reflectors) and deep (e.g., rocket/missile fairing) paraboloidal shells exhibit totally different modal actuation behaviors due to their curvature differences. Analytical results in this paper can serve as guidelines for optimal actuator placement for vibration control of different paraboloidal structures.
Calculation uncertainty of distribution-like parameters in NPP of PAKS
International Nuclear Information System (INIS)
Szecsenyi, Zsolt; Korpas, Layos
2000-01-01
In the reactor-physical point of view there were two important events in the Nuclear Power Plant of PAKS in this year. The Russian type profiled assemblies were loaded into the PAKS Unit 3, and new limitation system was introduced on the same Unit. It was required to solve a lot of problems because of these both events. One of these problems was the determination of uncertainty of quantities of the new limitation considering the fabrication uncertainties for the profiled assembly. The importance of determination of uncertainty is to guarantee on 99.9% level the avoidance of fuel failure. In this paper the principles of determination of calculation accuracy, applied methods and obtained results are presented in case of distribution-like parameters. A few elements of the method have been presented on earlier symposiums, so in this paper the whole method is just outlined. For example the GPT method was presented in the following paper: Uncertainty analysis of pin wise power distribution of WWER-440 assembly considering fabrication uncertainties. Finally in the summary of this paper additional intrinsic opportunities in the method are presented. (Authors)
Modeling the spatial distribution of the parameters of the coolant in the reactor volume
International Nuclear Information System (INIS)
Nikonov, S.P.
2011-01-01
In this paper the approach to the question about the spatial distribution of the parameters of the coolant in-reactor volume. To describe the in-core space is used specially developed preprocessor. When the work of the preprocessor in the first place, is recreated on the basis of available information (mostly-the original drawings) with high accuracy three-dimensional description of the structures of the reactor volume and, secondly, are prepared on this basis blocks input to the nodal system code improved estimate ATHLET, allows to take into account the hydrodynamic interaction between the spatial control volumes. As an example the special case of solutions of international standard problem on the reconstruction of the transition process in the third unit of the Kalinin nuclear power plant, due to the shutdown of one of the four Main Coolant Pumps in operation at the rated capacity (first download). Model-core area consists of approximately 58 000 control volumes and spatial relationships. It shows the influence of certain structural units of the core to the distribution of the mass floe rate of its height. It is detected a strong cross-flow coolant in the area over the baffle. Moreover, we study the distribution of the coolant temperature at the assembly head of WWER-1000 reactor. It is shown that in the region of the top of the assembly head, where we have installation of thermocouples, the flow coolant for internal assemblies core is formed by only from guide channel Reactor control and protected system Control rod flow, or a mixture of the guide channel flow and flow from the area in front of top grid head assembly (the peripheral assemblies). It is shown that the magnitude of the flow guide channels affects not only the position of control rods, but also the presence of a particular type of measuring channels (Self powered neutron detector sensors or Temperature control sensors) in the cassette. (Author)
International Nuclear Information System (INIS)
Fuoco, F.C.; Buonanno, G.; Stabile, L.; Vigo, P.
2014-01-01
Electronic cigarette-generated mainstream aerosols were characterized in terms of particle number concentrations and size distributions through a Condensation Particle Counter and a Fast Mobility Particle Sizer spectrometer, respectively. A thermodilution system was also used to properly sample and dilute the mainstream aerosol. Different types of electronic cigarettes, liquid flavors, liquid nicotine contents, as well as different puffing times were tested. Conventional tobacco cigarettes were also investigated. The total particle number concentration peak (for 2-s puff), averaged across the different electronic cigarette types and liquids, was measured equal to 4.39 ± 0.42 × 10 9 part. cm −3 , then comparable to the conventional cigarette one (3.14 ± 0.61 × 10 9 part. cm −3 ). Puffing times and nicotine contents were found to influence the particle concentration, whereas no significant differences were recognized in terms of flavors and types of cigarettes used. Particle number distribution modes of the electronic cigarette-generated aerosol were in the 120–165 nm range, then similar to the conventional cigarette one. -- Highlights: • High particle number concentrations measured in e-cigarettes' mainstream aerosol. • Particle concentrations were higher than conventional tobacco cigarette ones. • Nicotine content and puffing times influenced particle concentrations. • Flavoring and type of cigarette did not affect the particle number concentration. • Particle number distribution mode of e-cigarette aerosol was equal to 120–165 nm. -- The mainstream aerosol generated by electronic cigarettes was characterized and the effect of each operating parameter was evaluated: results were similar to conventional cigarette ones
Meshkat, Nicolette; Kuo, Christine Er-zhen; DiStefano, Joseph
2014-01-01
Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I-O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)-COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and-importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It's illustrated and validated here for models of moderate complexity, with
Energy Technology Data Exchange (ETDEWEB)
Meliopoulos, Sakis [Georgia Inst. of Technology, Atlanta, GA (United States); Cokkinides, George [Georgia Inst. of Technology, Atlanta, GA (United States); Fardanesh, Bruce [New York Power Authority, NY (United States); Hedrington, Clinton [U.S. Virgin Islands Water and Power Authority (WAPA), St. Croix (U.S. Virgin Islands)
2013-12-31
This is the final report for this project that was performed in the period: October1, 2009 to June 30, 2013. In this project, a fully distributed high-fidelity dynamic state estimator (DSE) that continuously tracks the real time dynamic model of a wide area system with update rates better than 60 times per second is achieved. The proposed technology is based on GPS-synchronized measurements but also utilizes data from all available Intelligent Electronic Devices in the system (numerical relays, digital fault recorders, digital meters, etc.). The distributed state estimator provides the real time model of the system not only the voltage phasors. The proposed system provides the infrastructure for a variety of applications and two very important applications (a) a high fidelity generating unit parameters estimation and (b) an energy function based transient stability monitoring of a wide area electric power system with predictive capability. Also the dynamic distributed state estimation results are stored (the storage scheme includes data and coincidental model) enabling an automatic reconstruction and “play back” of a system wide disturbance. This approach enables complete play back capability with fidelity equal to that of real time with the advantage of “playing back” at a user selected speed. The proposed technologies were developed and tested in the lab during the first 18 months of the project and then demonstrated on two actual systems, the USVI Water and Power Administration system and the New York Power Authority’s Blenheim-Gilboa pumped hydro plant in the last 18 months of the project. The four main thrusts of this project, mentioned above, are extremely important to the industry. The DSE with the achieved update rates (more than 60 times per second) provides a superior solution to the “grid visibility” question. The generator parameter identification method fills an important and practical need of the industry. The “energy function” based
International Nuclear Information System (INIS)
Kovacic, Ivana
2009-01-01
An analytical approach to determine the approximate solution for the periodic motion of non-conservative oscillators with a fractional-order restoring force and slowly varying parameters is presented. The solution has the form of the first-order differential equation for the amplitude and phase of motion. The method used is based on the combination of the Krylov-Bogoliubov method with Hamilton's variational principle with the uncommutative rule for the variation of velocity. The conservative systems with slowly varying parameters are also considered. The corresponding adiabatic invariant is obtained. Two examples are given to illustrate derived theoretical results.
Peters, B. C., Jr.; Walker, H. F.
1975-01-01
New results and insights concerning a previously published iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions were discussed. It was shown that the procedure converges locally to the consistent maximum likelihood estimate as long as a specified parameter is bounded between two limits. Bound values were given to yield optimal local convergence.
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Mohammad Zounemat-Kermani
2018-03-01
Full Text Available Chlorination unit is widely used to supply safe drinking water and removal of pathogens from water distribution networks. Data-driven approach is one appropriate method for analyzing performance of chlorine in water supply network. In this study, multi-layer perceptron neural network (MLP with three training algorithms (gradient descent, conjugate gradient and BFGS and support vector machine (SVM with RBF kernel function were used to predict the concentration of residual chlorine in water supply networks of Ahmadabad Dafeh and Ahruiyeh villages in Kerman Province. Daily data including discharge (flow, chlorine consumption and residual chlorine were employed from the beginning of 1391 Hijri until the end of 1393 Hijri (for 3 years. To assess the performance of studied models, the criteria such as Nash-Sutcliffe efficiency (NS, root mean square error (RMSE, mean absolute percentage error (MAPE and correlation coefficient (CORR were used that in best modeling situation were 0.9484, 0.0255, 1.081, and 0.974 respectively which resulted from BFGS algorithm. The criteria indicated that MLP model with BFGS and conjugate gradient algorithms were better than all other models in 90 and 10 percent of cases respectively; while the MLP model based on gradient descent algorithm and the SVM model were better in none of the cases. According to the results of this study, proper management of chlorine concentration can be implemented by predicted values of residual chlorine in water supply network. Thus, decreased performance of perceptron network and support vector machine in water supply network of Ahruiyeh in comparison to Ahmadabad Dafeh can be inferred from improper management of chlorination.
International Nuclear Information System (INIS)
Banerjee, Amit; Abu-Mahfouz, Issam
2014-01-01
The use of evolutionary algorithms has been popular in recent years for solving the inverse problem of identifying system parameters given the chaotic response of a dynamical system. The inverse problem is reformulated as a minimization problem and population-based optimizers such as evolutionary algorithms have been shown to be efficient solvers of the minimization problem. However, to the best of our knowledge, there has been no published work that evaluates the efficacy of using the two most popular evolutionary techniques – particle swarm optimization and differential evolution algorithm, on a wide range of parameter estimation problems. In this paper, the two methods along with their variants (for a total of seven algorithms) are applied to fifteen different parameter estimation problems of varying degrees of complexity. Estimation results are analyzed using nonparametric statistical methods to identify if an algorithm is statistically superior to others over the class of problems analyzed. Results based on parameter estimation quality suggest that there are significant differences between the algorithms with the newer, more sophisticated algorithms performing better than their canonical versions. More importantly, significant differences were also found among variants of the particle swarm optimizer and the best performing differential evolution algorithm
International Nuclear Information System (INIS)
Tunc Aldemir; Miller, Don W.; Hajek, Brian K.; Peng Wang
2002-01-01
The DSD (Dynamic System Doctor) is a system-independent, interactive software under development for on-line state/parameter estimation in dynamic systems (1), partially supported through a Nuclear Engineering Education (NEER) grant during 1998-2001. This paper summarizes the recent accomplishments in improving the user-friendliness and computational capability of DSD
Farokhi, Hamed; Païdoussis, Michael P.; Misra, Arun K.
2018-04-01
The present study examines the nonlinear behaviour of a cantilevered carbon nanotube (CNT) resonator and its mass detection sensitivity, employing a new nonlinear electrostatic load model. More specifically, a 3D finite element model is developed in order to obtain the electrostatic load distribution on cantilevered CNT resonators. A new nonlinear electrostatic load model is then proposed accounting for the end effects due to finite length. Additionally, a new nonlinear size-dependent continuum model is developed for the cantilevered CNT resonator, employing the modified couple stress theory (to account for size-effects) together with the Kelvin-Voigt model (to account for nonlinear damping); the size-dependent model takes into account all sources of nonlinearity, i.e. geometrical and inertial nonlinearities as well as nonlinearities associated with damping, small-scale, and electrostatic load. The nonlinear equation of motion of the cantilevered CNT resonator is obtained based on the new models developed for the CNT resonator and the electrostatic load. The Galerkin method is then applied to the nonlinear equation of motion, resulting in a set of nonlinear ordinary differential equations, consisting of geometrical, inertial, electrical, damping, and size-dependent nonlinear terms. This high-dimensional nonlinear discretized model is solved numerically utilizing the pseudo-arclength continuation technique. The nonlinear static and dynamic responses of the system are examined for various cases, investigating the effect of DC and AC voltages, length-scale parameter, nonlinear damping, and electrostatic load. Moreover, the mass detection sensitivity of the system is examined for possible application of the CNT resonator as a nanosensor.
Electron acoustic nonlinear structures in planetary magnetospheres
Shah, K. H.; Qureshi, M. N. S.; Masood, W.; Shah, H. A.
2018-04-01
In this paper, we have studied linear and nonlinear propagation of electron acoustic waves (EAWs) comprising cold and hot populations in which the ions form the neutralizing background. The hot electrons have been assumed to follow the generalized ( r , q ) distribution which has the advantage that it mimics most of the distribution functions observed in space plasmas. Interestingly, it has been found that unlike Maxwellian and kappa distributions, the electron acoustic waves admit not only rarefactive structures but also allow the formation of compressive solitary structures for generalized ( r , q ) distribution. It has been found that the flatness parameter r , tail parameter q , and the nonlinear propagation velocity u affect the propagation characteristics of nonlinear EAWs. Using the plasmas parameters, typically found in Saturn's magnetosphere and the Earth's auroral region, where two populations of electrons and electron acoustic solitary waves (EASWs) have been observed, we have given an estimate of the scale lengths over which these nonlinear waves are expected to form and how the size of these structures would vary with the change in the shape of the distribution function and with the change of the plasma parameters.
International Nuclear Information System (INIS)
Allafi, Walid; Uddin, Kotub; Zhang, Cheng; Mazuir Raja Ahsan Sha, Raja; Marco, James
2017-01-01
Highlights: •Off-line estimation approach for continuous-time domain for non-invertible function. •Model reformulated to multi-input-single-output; nonlinearity described by sigmoid. •Method directly estimates parameters of nonlinear ECM from the measured-data. •Iterative on-line technique leads to smoother convergence. •The model is validated off-line and on-line using NCA battery. -- Abstract: The accuracy of identifying the parameters of models describing lithium ion batteries (LIBs) in typical battery management system (BMS) applications is critical to the estimation of key states such as the state of charge (SoC) and state of health (SoH). In applications such as electric vehicles (EVs) where LIBs are subjected to highly demanding cycles of operation and varying environmental conditions leading to non-trivial interactions of ageing stress factors, this identification is more challenging. This paper proposes an algorithm that directly estimates the parameters of a nonlinear battery model from measured input and output data in the continuous time-domain. The simplified refined instrumental variable method is extended to estimate the parameters of a Wiener model where there is no requirement for the nonlinear function to be invertible. To account for nonlinear battery dynamics, in this paper, the typical linear equivalent circuit model (ECM) is enhanced by a block-oriented Wiener configuration where the nonlinear memoryless block following the typical ECM is defined to be a sigmoid static nonlinearity. The nonlinear Weiner model is reformulated in the form of a multi-input, single-output linear model. This linear form allows the parameters of the nonlinear model to be estimated using any linear estimator such as the well-established least squares (LS) algorithm. In this paper, the recursive least square (RLS) method is adopted for online parameter estimation. The approach was validated on experimental data measured from an 18650-type Graphite
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P Bhattacharya
2016-09-01
Full Text Available The wind resource varies with of the day and the season of the year and even some extent from year to year. Wind energy has inherent variances and hence it has been expressed by distribution functions. In this paper, we present some methods for estimating Weibull parameters in case of a low wind speed characterization, namely, shape parameter (k, scale parameter (c and characterize the discrete wind data sample by the discrete Hilbert transform. We know that the Weibull distribution is an important distribution especially for reliability and maintainability analysis. The suitable values for both shape parameter and scale parameters of Weibull distribution are important for selecting locations of installing wind turbine generators. The scale parameter of Weibull distribution also important to determine whether a wind farm is good or not. Thereafter the use of discrete Hilbert transform (DHT for wind speed characterization provides a new era of using DHT besides its application in digital signal processing. Basically in this paper, discrete Hilbert transform has been applied to characterize the wind sample data measured on College of Engineering and Management, Kolaghat, East Midnapore, India in January 2011.
Wu, Han; Jiang, Baofa; Zhu, Ping; Geng, Xingyi; Liu, Zhong; Cui, Liangliang; Yang, Liping
2018-02-01
When discussing the association between birth weight and air pollution, previous studies mainly focus on the maternal trimester-specific exposures during pregnancy, whereas the possible associations between birth weight and weekly-specific exposures have been largely neglected. We conducted a nested 1:4 matched case-control study in Jinan, China to examine the weekly-specific associations during pregnancy between maternal fine particulate matter (aerodynamic diameter gender-, gestational age-, and parity-specific standard score (BWGAP z-score) was calculated as the outcome of interest. Distributed lag non-linear models (DLNMs) were applied to estimate weekly-specific relationship between maternal air pollutant exposures and birth weight. For an increase of per inter-quartile range in maternal PM2.5 exposure concentration during pregnancy, the BWGAP z-score decreased significantly during the 27th-33th gestational weeks with the strongest association in the 30th gestational weeks (standard deviation units decrease in BWGAP z-score: -0.049, 95% CI: -0.080 -0.017, in three-pollutant model). No significant association between maternal weekly NO2 or SO2 BWGAP z-score was observed. In conclusion, this study provides evidence that maternal PM2.5 exposure during the 27th-33th gestational weeks may reduce the birth weight in the context of very high pollution level of PM2.5.
Directory of Open Access Journals (Sweden)
E. Baümler
2014-06-01
Full Text Available In this study the kinetics of oil extraction from partially dehulled safflower seeds under two moisture conditions (7 and 9% dry basis was investigated. The extraction assays were performed using a stirred batch system, thermostated at 50 ºC, using n-hexane as solvent. The data obtained were fitted to a modified diffusion model in order to represent the extraction kinetics. The model took into account a washing and a diffusive step. Fitting parameters were compared statistically for both moisture conditions. The oil yield increased with the extraction time in both cases, although the oil was released at different rates. A comparison of the parameters showed that both the portion extracted in the washing phase and the effective diffusion coefficient were moisture-dependent. The effective diffusivities were 2.81 10-12 and 8.06 10-13 m²s-1 for moisture contents of 7% and 9%, respectively.
Energy Technology Data Exchange (ETDEWEB)
Serkez, Svitozar; Kocharyan, Vitali; Saldin, Evgeni; Zagorodnov, Igor [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Geloni, Gianluca [European XFEL GmbH, Hamburg (Germany)
2013-09-15
We demonstrate that the output radiation characteristics of the European XFEL sources at nominal operation point can be easily made significantly better than what is currently reported in the TDRs of scientific instruments and X-ray optics. In fact, the output SASE characteristics of the baseline European XFEL have been previously optimized assuming uniform undulators at a nominal operating point of 5 kA peak current, without considering the potential of undulator tapering in the SASE regime. In order to illustrate this point, we analyze the case of an electron bunch with nominal parameters. Based on start-to-end simulations, we demonstrate that nonlinear undulator tapering allows one to achieve up to a tenfold increase in peak power and photon spectral density in the conventional SASE regime, without modification to the baseline design. The FEL code Genesis has been extensively used for these studies. In order to increase our confidence in simulation results, we cross-checked outcomes by reproducing simulations in the deep nonlinear SASE regime with tapered undulator using the code ALICE.
Westinghouse-GOTHIC distributed parameter modelling for HDR test E11.2
International Nuclear Information System (INIS)
Narula, J.S.; Woodcock, J.
1994-01-01
The Westinghouse-GOTHIC (WGOTHIC) code is a sophisticated mathematical computer code designed specifically for the thermal hydraulic analysis of nuclear power plant containment and auxiliary buildings. The code is capable of sophisticated flow analysis via the solution of mass, momentum, and energy conservation equations. Westinghouse has investigated the use of subdivided noding to model the flow patterns of hydrogen following its release into a containment atmosphere. For the investigation, several simple models were constructed to represent a scale similar to the German HDR containment. The calculational models were simplified to test the basic capability of the plume modeling methods to predict stratification while minimizing the number of parameters. A large empty volume was modeled, with the same volume and height as HDR. A scenario was selected that would be expected to stably stratify, and the effects of noding on the prediction of stratification was studied. A single phase hot gas was injected into the volume at a height similar to that of HDR test E11.2, and there were no heat sinks modeled. Helium was released into the calculational models, and the resulting flow patterns were judged relative to the expected results. For each model, only the number of subdivisions within the containment volume was varied. The results of the investigation of noding schemes has provided evidence of the capability of subdivided (distributed parameter) noding. The results also showed that highly inaccurate flow patterns could be obtained by using an insufficient number of subdivided nodes. This presents a significant challenge to the containment analyst, who must weigh the benefits of increased noding with the penalties the noding may incur on computational efficiency. Clearly, however, an incorrect noding choice may yield erroneous results even if great care has been taken in modeling accurately all other characteristics of containments. (author). 9 refs., 9 figs
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E. KRASAKOPOULOU
2006-06-01
Full Text Available Data on the distribution of dissolved inorganic carbon (measured as TCO2 and related parameters in the Thermaikos Gulf were obtained during May 1997. High TCO2 concentrations were recorded close to the bottom, especially in the northern part of the gulf, as a result of organic matter remineralisation. The positive relatively good correlation between TCO2 and both apparent oxygen utilisation (AOU and phosphate at the last sampling depth confi rmed the regenerative origin of a large proportion of TCO2. The comparatively conservative behaviour of alkalinity, together with the relatively low value of the homogenous buffer factor β (β = ∂lnfCO2/∂lnTCO2 revealed that calcifi cation or carbonate dissolution takes place on a very small scale, simultaneously with the organic carbon production. The correlations between fCO2 and chlorophyll α, as well as AOU and the surface temperature, revealed that the carbon dioxide fi xation through the biological activity is the principal factor that modulates the variability of fCO2. A rough first estimate of the magnitude of the air-sea CO2 exchange and the potential role of the Thermaikos Gulf in the transfer of atmospheric CO2 was also obtained. The results showed that during May 1997, the Thermaikos Gulf acted as a weak sink for atmospheric CO2 at a rate of -0.60 - -1.43 mmol m-2 d-1, depending on which formula for the gas transfer velocity was used, and in accordance to recent reports regarding other temperate continental shelves. Extensive study of the dissolved inorganic carbon and related parameters, and continuous shipboard measurements of fCO2 a and fCO2 w during all seasons are necessary to safely quantify the role of the Thermaikos Gulf in the context of the coastal margins CO2 dynamics.
International Nuclear Information System (INIS)
Nath, Samuel; Dere, Ashlee
2016-01-01
Bacillus anthracis is the pathogenic bacterium that causes anthrax, which dwells in soils as highly resilient endospores. B. anthracis spore viability in soil is dependent upon environmental conditions, but the soil properties necessary for spore survival are unclear. In this study we used a range of soil geochemical and physical parameters to predict the spatial distribution of B. anthracis in northwest Minnesota, where 64 cases of anthrax in livestock were reported from 2000 to 2013. Two modeling approaches at different spatial scales were used to identify the soil conditions most correlated to known anthrax cases using both statewide and locally collected soil data. Ecological niche models were constructed using the Maximum Entropy (Maxent) approach and included 11 soil parameters as environmental inputs and recorded anthrax cases as known presences. One ecological niche model used soil data and anthrax presences for the entire state while a second model used locally sampled soil data (n = 125) and a subset of anthrax presences, providing a test of spatial scale. In addition, simple logistic regression models using the localized soil data served as an independent measure of variable importance. Maxent model results indicate that at a statewide level, soil calcium and magnesium concentrations, soil pH, and sand content are the most important properties for predicting soil suitability for B. anthracis while at the local level, clay and sand content along with phosphorous and strontium concentrations are most important. These results also show that the spatial scale of analysis is important when considering soil parameters most important for B. anthracis spores. For example, at a broad scale, B. anthracis spores may require Ca-rich soils and an alkaline pH, but may also concentrate in microenvironments with high Sr concentrations. The study is also one of the first ecological niche models that demonstrates the major importance of soil texture for defining
International Nuclear Information System (INIS)
Zhidkov, P.E.
1996-01-01
First, the eigenvalue problem on the segment [0,1] for the Sturm-Liouville operator with a potential depending on the spectral parameter with the zero Dirichlet boundary conditions is considered. For this problem, under some hypotheses on the potential, it is proved that the necessary and sufficient condition for an arbitrary system of eigenfunctions, possessing a unique function with n roots in the interval (0,1) for an arbitrary non-negative integer number n, being complete in the space L 2 (0,1) is the linear independence of the functions from this system in the space L 2 (0,1). Then, this result is applied to the investigation of an eigenvalue problem for a nonlinear operator on the Sturm-Liouville type. For this problem, the completeness of the system of its eigenfunctions in the space L 2 (0,1) is proved. (author). 12 refs
Hua, Changchun; Zhang, Liuliu; Guan, Xinping
2017-01-01
This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.
Effect of geometrical parameters on pressure distributions of impulse manufacturing technologies
Brune, Ryan Carl
major and minor strains for each sample type to compare limit strain results. Overall testing indicated decreased formability at high velocity for 304 DDQ stainless steel and increased formability at high velocity for 3003-H14 aluminum. Microstructural and fractographic analysis helped dissect and analyze the observed differences in these cases. Overall, these studies comprehensively explore the effects of geometrical parameters on magnitude and distribution of impulse manufacturing generated pressure, establishing key guidelines and models for continued development and implementation in commercial applications.
Linking particle and pore-size distribution parameters to soil gas transport properties
DEFF Research Database (Denmark)
Arthur, Emmanuel; Møldrup, Per; Schjønning, Per
2012-01-01
, respectively) and the Campbell water retention parameter b were used to characterize particle and pore size distributions, respectively. Campbell b yielded a wide interval (4.6–26.2) and was highly correlated with α, β, and volumetric clay content. Both Dp/Do and ka followed simple power-law functions (PLFs......) of air-filled porosity (εa). The PLF tortuosity–connectivity factors (X*) for Dp/Do and ka were both highly correlated with all basic soil characteristics, in the order of volumetric clay content = Campbell b > gravimetric clay content > α > β. The PLF water blockage factors (H) for Dp/Do and ka were...... also well (but relatively more weakly) correlated with the basic soil characteristics, again with the best correlations to volumetric clay content and b. As a first attempt at developing a simple Dp/Do model useful at the field scale, we extended the classical Buckingham Dp/Do model (εa2) by a scaling...
Krishnasamy, M.; Qian, Feng; Zuo, Lei; Lenka, T. R.
2018-03-01
The charge cancellation due to the change of strain along single continuous piezoelectric layer can remarkably affect the performance of a cantilever based harvester. In this paper, analytical models using distributed parameters are developed with some extent of averting the charge cancellation in cantilever piezoelectric transducer where the piezoelectric layers are segmented at strain nodes of concerned vibration mode. The electrode of piezoelectric segments are parallelly connected with a single external resistive load in the 1st model (Model 1). While each bimorph piezoelectric layers are connected in parallel to a resistor to form an independent circuit in the 2nd model (Model 2). The analytical expressions of the closed-form electromechanical coupling responses in frequency domain under harmonic base excitation are derived based on the Euler-Bernoulli beam assumption for both models. The developed analytical models are validated by COMSOL and experimental results. The results demonstrate that the energy harvesting performance of the developed segmented piezoelectric layer models is better than the traditional model of continuous piezoelectric layer.
Directory of Open Access Journals (Sweden)
Kexin Wang
2018-03-01
Full Text Available In water-quality, early warning systems and qualitative detection of contaminants are always challenging. There are a number of parameters that need to be measured which are not entirely linearly related to pollutant concentrations. Besides the complex correlations between variable water parameters that need to be analyzed also impairs the accuracy of quantitative detection. In aspects of these problems, the application of least-squares support vector machines (LS-SVM is used to evaluate the water contamination and various conventional water quality sensors quantitatively. The various contaminations may cause different correlative responses of sensors, and also the degree of response is related to the concentration of the injected contaminant. Therefore to enhance the reliability and accuracy of water contamination detection a new method is proposed. In this method, a new relative response parameter is introduced to calculate the differences between water quality parameters and their baselines. A variety of regression models has been examined, as result of its high performance, the regression model based on genetic algorithm (GA is combined with LS-SVM. In this paper, the practical application of the proposed method is considered, controlled experiments are designed, and data is collected from the experimental setup. The measured data is applied to analyze the water contamination concentration. The evaluation of results validated that the LS-SVM model can adapt to the local nonlinear variations between water quality parameters and contamination concentration with the excellent generalization ability and accuracy. The validity of the proposed approach in concentration evaluation for potassium ferricyanide is proven to be more than 0.5 mg/L in water distribution systems.
International Nuclear Information System (INIS)
Chu Yuntao; Lou Chun; Cheng Qiang; Zhou Huaichun
2008-01-01
In this paper, a dynamic, distributed parameter model for the evaporation system of a controlled circulation boiler was developed. As an essential basis, the 3-D temperature distribution and the average emissivity of the particle phase inside its furnace can be got by a flame image processing technique from multiple, visible flame image detectors in a real-time combustion monitoring system. Then the transient, 2-D radiation flux can be obtained by solving a set of energy balance equations for the water wall elements, which serves as a distributed boundary condition for the dynamic, distributed parameter model proposed for the evaporation system. For large change of the boiler load, two important parameters, the correction factor of equivalent flame emissivity and the coefficient of the steam mass flow rate at the outlet of the drum, were determined using the operation data from a 300 MW boiler. The model was validated by comparing the simulation results for some main steam parameters of the system with those from measurements. Besides that, the transient distributions of the parameters, such as the steam quality and the mass velocity, were predicted by the model. This model can be used for on-line calculation or off-line prediction of the local abnormal phenomena occurring on the water walls, forming an important basis to effectively evaluate the security and the reliability of a power plant boiler
A new approach to nonlinear constrained Tikhonov regularization
Ito, Kazufumi
2011-09-16
We present a novel approach to nonlinear constrained Tikhonov regularization from the viewpoint of optimization theory. A second-order sufficient optimality condition is suggested as a nonlinearity condition to handle the nonlinearity of the forward operator. The approach is exploited to derive convergence rate results for a priori as well as a posteriori choice rules, e.g., discrepancy principle and balancing principle, for selecting the regularization parameter. The idea is further illustrated on a general class of parameter identification problems, for which (new) source and nonlinearity conditions are derived and the structural property of the nonlinearity term is revealed. A number of examples including identifying distributed parameters in elliptic differential equations are presented. © 2011 IOP Publishing Ltd.
Razzaq, Javaria; Haque, Q.; Khan, Majid; Bhatti, Adnan Mehmood; Kamran, M.; Mirza, Arshad M.
2018-02-01
Nonlinear structure formation in ion-temperature-gradient (ITG) driven waves is investigated in pair-ion plasma comprising ions and nonthermal electrons (kappa, Cairns). By using the transport equations of the Braginskii model, a new set of nonlinear equations are derived. A linear dispersion relation is obtained and discussed analytically as well as numerically. It is shown that the nonthermal population of electrons affects both the linear and nonlinear characteristics of the ITG mode in pair-ion plasma. This work will be useful in tokamaks and stellarators where non-Maxwellian population of electrons may exist due to resonant frequency heating, electron cyclotron heating, runaway electrons, etc.
International Nuclear Information System (INIS)
Jiang Zheng-Xian; Cui Bao-Tong; Lou Xu-Yang; Zhuang Bo
2017-01-01
In this paper, the control problem of distributed parameter systems is investigated by using wireless sensor and actuator networks with the observer-based method. Firstly, a centralized observer which makes use of the measurement information provided by the fixed sensors is designed to estimate the distributed parameter systems. The mobile agents, each of which is affixed with a controller and an actuator, can provide the observer-based control for the target systems. By using Lyapunov stability arguments, the stability for the estimation error system and distributed parameter control system is proved, meanwhile a guidance scheme for each mobile actuator is provided to improve the control performance. A numerical example is finally used to demonstrate the effectiveness and the advantages of the proposed approaches. (paper)
Robust methods and asymptotic theory in nonlinear econometrics
Bierens, Herman J
1981-01-01
This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and non linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate ...
Ortega, Ileana; Martín, Alberto; Díaz, Yusbelly
2011-03-01
Astropecten marginatus is a sea star widely distributed in Northern and Eastern South America, found on sandy and muddy bottoms, in shallow and deep waters. To describe some of its ecological characteristics, we calculated it spatial-temporal distribution, population parameters (based on size and weight) and diet in the Orinoco Delta ecoregion (Venezuela). The ecoregion was divided in three sections: Golfo de Paria, Boca de Serpiente and Plataforma Deltana. Samples for the rainy and dry seasons came from megabenthos surveys of the "Línea Base Ambiental Plataforma Deltana (LBAPD)" and "Corocoro Fase I (CFI)" projects. The collected sea stars were measured, weighted and dissected by the oral side to extract their stomach and identify the preys consumed. A total of 570 sea stars were collected in LBAPD project and 306 in CFI one. The highest densities were found during the dry season in almost all sections. In LBAPD project the highest density was in "Plataforma Deltana" section (0.007 +/- 0.022 ind/m2 in dry season and 0.014 +/- 0.06 ind/m2 in rainy season) and in the CFI project the densities in "Golfo de Paria" section were 0.705 +/- 0.829 ind/m2 in rainy season and 1.027 +/- 1.107 ind/m2 in dry season. The most frequent size range was 3.1-4.6cm. The highest biomass was found in "Golfo de Paria" section (7.581 +/- 0.018 mg/m2 in dry season and 0.005 +/- 6.542 x 10(-06) mg/m2 in rainy season for 2004-2005 and 3.979 +/- 4.024 mg/m2 in dry season; and 3.117 +/- 3.137 mg/m2 in rainy season for 2006). A linear relationship was found between the sea star size and its weight but no relationship was observed between its size and the depth where it was collected. Mollusks are dominant in the sea star diet (47.4% in abundance). The diet in any of the sections, seasons or between projects or size class was heterogeneous, using multivariate ordinations (MDS) and SIMPER analysis and there was no difference in the prey number or food elements that a sea star can eat. Although A
Directory of Open Access Journals (Sweden)
Koen Degeling
2017-12-01
Full Text Available Abstract Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Methods Two approaches, 1 using non-parametric bootstrapping and 2 using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Results Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500, the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25, yielding infeasible modeling outcomes. Conclusions Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.
Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik
2017-12-15
Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.
Banks, H. T.; Ito, K.
1988-01-01
Numerical techniques for parameter identification in distributed-parameter systems are developed analytically. A general convergence and stability framework (for continuous dependence on observations) is derived for first-order systems on the basis of (1) a weak formulation in terms of sesquilinear forms and (2) the resolvent convergence form of the Trotter-Kato approximation. The extension of this framework to second-order systems is considered.
International Nuclear Information System (INIS)
Garnadi, A.D.
1997-01-01
In the distributed parameter systems with exponential feedback, non-global existence of solution is not always exist. For some positive initial values, there exist finite time T such that the solution goes to infinity, i.e. finite time extinction or blow-up. Here is present a numerical solution using Moving Mesh Finite Element to solve the distributed parameter systems with exponential feedback close to blow-up time. The numerical behavior of the mesh close to the time of extinction is the prime interest in this study
International Nuclear Information System (INIS)
Vishnyakova, T.P.; Klychev, Sh.I.
1992-01-01
The use of optical mixers in the optical irradiators of simulators of direct and concentrated solar radiation has been proposed. In this paper, the parameters of an optical mixer are calculated geometrically, and the effect of the parameters of the optical mixer on the unformity of the irradiance distribution η of the radiation flux on the detector is investigated. These investigations show that the light distribution from an optical mixer is close to the characteristics of an ideal uniform emitter within the region from 0 to the limit of α. 5 refs., 4 figs
Mahmoud, Emad E.; Abood, Fatimah S.
In this paper, we will demonstrate the adaptive complex anti-lag synchronization (CALS) of two indistinguishable complex chaotic nonlinear systems with the parameters which are uncertain. The significance of CALS is not advised well in the literature yet. The CALS contains or consolidate two sorts of synchronizations (anti-lag synchronization ALS and lag synchronization LS). The state variable of the master system synchronizes with an alternate state variable of the slave system. Depending on the function of Lyapunov, a plan is orchestrated to achieve CALS of chaotic attractors of complex systems with unverifiable parameters. CALS of two indistinguishable complexes of Lü systems is viewed as, for example, an occasion for affirming the likelihood of the plan exhibited. In physics, we can see complex chaotic systems in numerous different applications, for example, applied sciences or engineering. With a specific end goal to affirm the proposed synchronization plan viability and demonstrate the hypothetical outcomes, we can compute the numerical simulation. The above outcomes will give the hypothetical establishment to the secure communication applications. CALS of complex chaotic systems in which a state variable of the master system synchronizes with an alternate state variable of the slave system is an encouraging sort of synchronization as it contributes excellent security in secure communication. Amid this secure communication, the synchronization between transmitter and collector is shut and message signals are recouped. The encryption and restoration of the signals are simulated numerically.
International Nuclear Information System (INIS)
Liu Guoqiang; Yan Changqi; Tian Daogui; Sun Licheng
2014-01-01
Experimental study was performed on distribution characteristics of interfacial parameters of downward gas-liquid flow in a vertical circular tube with the measurement by a two-sensor optical fiber probe. The test section is a circular pipe with the inner diameter of 50 mm and the length of 2000 mm. The superficial velocities of the gas and the liquid phases cover the ranges of 0.004-0.077 m/s and 0.43-0.71 m/s, respectively. The results show that the distributions of the interfacial parameters in downward bubbly flows are quite different from those in upward bubbly flows. For the case of upward flow, the parameters present the 'wall-peak' or 'core-peak' distributions, but for the case of downward flow, they show 'wall-peak' or 'wide-peak' distributions. The average value of void fraction in vertical downward flow is about 119.6%-145.0% larger than that in upward flow, and the interfacial area concentration is about 18.8%-82.5% larger than that in upward flow. The distribution of interfacial parameters shows an obvious tendency of uniformity. (authors)
Jurgens, Bryant; Böhlke, John Karl; Kauffman, Leon J.; Belitz, Kenneth; Esser, Bradley K.
2016-01-01
A partial exponential lumped parameter model (PEM) was derived to determine age distributions and nitrate trends in long-screened production wells. The PEM can simulate age distributions for wells screened over any finite interval of an aquifer that has an exponential distribution of age with depth. The PEM has 3 parameters – the ratio of saturated thickness to the top and bottom of the screen and mean age, but these can be reduced to 1 parameter (mean age) by using well construction information and estimates of the saturated thickness. The PEM was tested with data from 30 production wells in a heterogeneous alluvial fan aquifer in California, USA. Well construction data were used to guide parameterization of a PEM for each well and mean age was calibrated to measured environmental tracer data (3H, 3He, CFC-113, and 14C). Results were compared to age distributions generated for individual wells using advective particle tracking models (PTMs). Age distributions from PTMs were more complex than PEM distributions, but PEMs provided better fits to tracer data, partly because the PTMs did not simulate 14C accurately in wells that captured varying amounts of old groundwater recharged at lower rates prior to groundwater development and irrigation. Nitrate trends were simulated independently of the calibration process and the PEM provided good fits for at least 11 of 24 wells. This work shows that the PEM, and lumped parameter models (LPMs) in general, can often identify critical features of the age distributions in wells that are needed to explain observed tracer data and nonpoint source contaminant trends, even in systems where aquifer heterogeneity and water-use complicate distributions of age. While accurate PTMs are preferable for understanding and predicting aquifer-scale responses to water use and contaminant transport, LPMs can be sensitive to local conditions near individual wells that may be inaccurately represented or missing in an aquifer-scale flow model.
International Nuclear Information System (INIS)
Keall, P J; Webb, S
2007-01-01
The heterogeneity of human tumour radiation response is well known. Researchers have used the normal distribution to describe interpatient tumour radiosensitivity. However, many natural phenomena show a log-normal distribution. Log-normal distributions are common when mean values are low, variances are large and values cannot be negative. These conditions apply to radiosensitivity. The aim of this work was to evaluate the log-normal distribution to predict clinical tumour control probability (TCP) data and to compare the results with the homogeneous (δ-function with single α-value) and normal distributions. The clinically derived TCP data for four tumour types-melanoma, breast, squamous cell carcinoma and nodes-were used to fit the TCP models. Three forms of interpatient tumour radiosensitivity were considered: the log-normal, normal and δ-function. The free parameters in the models were the radiosensitivity mean, standard deviation and clonogenic cell density. The evaluation metric was the deviance of the maximum likelihood estimation of the fit of the TCP calculated using the predicted parameters to the clinical data. We conclude that (1) the log-normal and normal distributions of interpatient tumour radiosensitivity heterogeneity more closely describe clinical TCP data than a single radiosensitivity value and (2) the log-normal distribution has some theoretical and practical advantages over the normal distribution. Further work is needed to test these models on higher quality clinical outcome datasets
Directory of Open Access Journals (Sweden)
Simon van Mourik
2014-06-01
Full Text Available Multi-parameter models in systems biology are typically ‘sloppy’: some parameters or combinations of parameters may be hard to estimate from data, whereas others are not. One might expect that parameter uncertainty automatically leads to uncertain predictions, but this is not the case. We illustrate this by showing that the prediction uncertainty of each of six sloppy models varies enormously among different predictions. Statistical approximations of parameter uncertainty may lead to dramatic errors in prediction uncertainty estimation. We argue that prediction uncertainty assessment must therefore be performed on a per-prediction basis using a full computational uncertainty analysis. In practice this is feasible by providing a model with a sample or ensemble representing the distribution of its parameters. Within a Bayesian framework, such a sample may be generated by a Markov Chain Monte Carlo (MCMC algorithm that infers the parameter distribution based on experimental data. Matlab code for generating the sample (with the Differential Evolution Markov Chain sampler and the subsequent uncertainty analysis using such a sample, is supplied as Supplemental Information.
Analysis and design of robust decentralized controllers for nonlinear systems
Energy Technology Data Exchange (ETDEWEB)
Schoenwald, D.A.
1993-07-01
Decentralized control strategies for nonlinear systems are achieved via feedback linearization techniques. New results on optimization and parameter robustness of non-linear systems are also developed. In addition, parametric uncertainty in large-scale systems is handled by sensitivity analysis and optimal control methods in a completely decentralized framework. This idea is applied to alleviate uncertainty in friction parameters for the gimbal joints on Space Station Freedom. As an example of decentralized nonlinear control, singular perturbation methods and distributed vibration damping are merged into a control strategy for a two-link flexible manipulator.
File management for experiment control parameters within a distributed function computer network
International Nuclear Information System (INIS)
Stubblefield, F.W.
1976-10-01
An attempt to design and implement a computer system for control of and data collection from a set of laboratory experiments reveals that many of the experiments in the set require an extensive collection of parameters for their control. The operation of the experiments can be greatly simplified if a means can be found for storing these parameters between experiments and automatically accessing them as they are required. A subsystem for managing files of such experiment control parameters is discussed. 3 figures
The sensitivity of a water distribution system to regional state parameter variations
CSIR Research Space (South Africa)
Page, Philip R
2018-05-01
Full Text Available ]. The following types of parameters fall in each category: Proportional Change Parameters 𝑋𝑖. (i) Pipe lengths 𝐿 (ii) Pipe diameters𝐷 (iii) Pipe roughness coefficients 𝐶 (Hazen-Williams), 𝑁 (Chezy-Manning) or for Darcy-Weisbach (iv) Minor loss coefficients... for the case where there is a single state parameter region. 5. Pipe Parameter Scaling Laws Assume that the major friction loss in a pipe is described by either the Hazen-Williams (H-W) or Chezy-Manning (C-M) formulae (defined in the Appendix), with 𝐶 and𝑁...
International Nuclear Information System (INIS)
Niemiec, W.
1985-01-01
A constitutive mathematical model of distributed parameters of multicomponent chemical processes in gas, fluid and solid phase is utilized to the realization of phenomenal distributed parameter control of these processes. Original systems of partial differential constitutive state equations, in the following derivative forms /I/, /II/ and /III/ are solved in this paper from the point of view of information for phenomenal distributed parameter control of considered processes. Obtained in this way for multicomponent chemical processes in gas, fluid and solid phase: -dynamical working space-time characteristics/analytical solutions in working space-time of chemical reactors/, -dynamical phenomenal Green functions as working space-time transfer functions, -statical working space characteristics /analytical solutions in working space of chemical reactors/, -statical phenomenal Green functions as working space transfer functions, are applied, as information for realization of constitutive distributed parameter control of mass, energy and momentum aspects of above processes. Two cases are considered by existence of: A/sup o/ - initial conditions, B/sup o/ - initial and boundary conditions, for multicomponent chemical processes in gas, fluid and solid phase
Directory of Open Access Journals (Sweden)
Sanjay Kumar Singh
2011-06-01
Full Text Available In this Paper we propose Bayes estimators of the parameters of Exponentiated Exponential distribution and Reliability functions under General Entropy loss function for Type II censored sample. The proposed estimators have been compared with the corresponding Bayes estimators obtained under Squared Error loss function and maximum likelihood estimators for their simulated risks (average loss over sample space.
Seslija, Marko; van der Schaft, Arjan; Scherpen, Jacquelien M.A.
This paper addresses the issue of structure-preserving discretization of open distributed-parameter systems with Hamiltonian dynamics. Employing the formalism of discrete exterior calculus, we introduce a simplicial Dirac structure as a discrete analogue of the Stokes-Dirac structure and demonstrate
Seslija, Marko; Scherpen, Jacquelien M.A.; van der Schaft, Arjan
2011-01-01
This paper addresses the issue of structure-preserving discretization of open distributed-parameter systems with Hamiltonian dynamics. Employing the formalism of discrete exterior calculus, we introduce simplicial Dirac structures as discrete analogues of the Stokes-Dirac structure and demonstrate
International Nuclear Information System (INIS)
Baum, C; Alber, M; Birkner, M; Nuesslin, F
2004-01-01
Geometric uncertainties arise during treatment planning and treatment and mean that dose-dependent parameters such as EUD are random variables with a patient specific probability distribution. Treatment planning with highly conformal treatment techniques such as intensity modulated radiation therapy requires new evaluation tools which allow us to estimate this influence of geometrical uncertainties on the probable treatment dose for a planned dose distribution. Monte Carlo simulations of treatment courses with recalculation of the dose according to the daily geometric errors are a gold standard for such an evaluation. Distribution histograms which show the relative frequency of a treatment quality parameter in the treatment simulations can be used to evaluate the potential risks and chances of a planned dose distribution. As treatment simulations with dose recalculation are very time consuming for sufficient statistical accuracy, it is proposed to do treatment simulations in the dose parameter space where the result is mainly determined by the systematic and random component of the geometrical uncertainties. Comparison of the parameter space simulation method with the gold standard for prostate cases and a head and neck case shows good agreement as long as the number of fractions is high enough and the influence of tissue inhomogeneities and surface curvature on the dose is small
Directory of Open Access Journals (Sweden)
Chris Bambey Guure
2012-01-01
Full Text Available The Weibull distribution has been observed as one of the most useful distribution, for modelling and analysing lifetime data in engineering, biology, and others. Studies have been done vigorously in the literature to determine the best method in estimating its parameters. Recently, much attention has been given to the Bayesian estimation approach for parameters estimation which is in contention with other estimation methods. In this paper, we examine the performance of maximum likelihood estimator and Bayesian estimator using extension of Jeffreys prior information with three loss functions, namely, the linear exponential loss, general entropy loss, and the square error loss function for estimating the two-parameter Weibull failure time distribution. These methods are compared using mean square error through simulation study with varying sample sizes. The results show that Bayesian estimator using extension of Jeffreys' prior under linear exponential loss function in most cases gives the smallest mean square error and absolute bias for both the scale parameter α and the shape parameter β for the given values of extension of Jeffreys' prior.
The Effect of Stiffness Parameter on Mass Distribution in Heavy-Ion Induced Fission
Soheyli, Saeed; Khalil Khalili, Morteza; Ashrafi, Ghazaaleh
2018-06-01
The stiffness parameter of the composite system has been studied for several heavy-ion induced fission reactions without the contribution of non-compound nucleus fission events. In this research, determination of the stiffness parameter is based on the comparison between the experimental data on the mass widths of fission fragments and those predicted by the statistical model treatments at the saddle and scission points. Analysis of the results shows that for the induced fission reactions of different targets by the same projectile, the stiffness parameter of the composite system decreases with increasing the fissility parameter, as well as with increasing the mass number of the compound nucleus. This parameter also exhibits a similar behavior for the reactions of a given target induced by different projectiles. As expected, nearly same stiffness values are obtained for different reactions leading to the same compound nucleus.
International Nuclear Information System (INIS)
Grobnic, D.; Popescu, I.M.
1993-01-01
As a result of their granular structure the conductance of ceramic high temperature superconductors depends strongly on the characteristics of the parameter distribution. To study the influence of these distributions of the magneto-resistive transition from normal to superconductive state, a mathematical model was used. This model simulates the superconductor sample, considered as large three-dimensional collection of Josephson tunnel junctions. Each individual junction, according to the values of the parameters that define it, in a given environment (temperature, magnetic field and current density) allows or not the supercurrent to flow with a given probability. The bond percolation problem was solved using a Monte Carlo procedure. To solve the random resistor network formed, a sparse matrix package was used. As parameters that defined Josephson junction which choose the resistance of the normal junction state and the critical temperature of the grain. We considered the normal junction resistance as obeying a log normal distribution and the critical temperature, a Gaussian one. The influences of the relative dispersion of the first distribution and the dispersion of the critical temperature distribution on the shape of the resistivity versus magnetic field was studied. (Author)
Wave propagation in elastic medium with heterogeneous quadratic nonlinearity
International Nuclear Information System (INIS)
Tang Guangxin; Jacobs, Laurence J.; Qu Jianmin
2011-01-01
This paper studies the one-dimensional wave propagation in an elastic medium with spatially non-uniform quadratic nonlinearity. Two problems are solved analytically. One is for a time-harmonic wave propagating in a half-space where the displacement is prescribed on the surface of the half-space. It is found that spatial non-uniformity of the material nonlinearity causes backscattering of the second order harmonic, which when combined with the forward propagating waves generates a standing wave in steady-state wave motion. The second problem solved is the reflection from and transmission through a layer of finite thickness embedded in an otherwise linearly elastic medium of infinite extent, where it is assumed that the layer has a spatially non-uniform quadratic nonlinearity. The results show that the transmission coefficient for the second order harmonic is proportional to the spatial average of the nonlinearity across the thickness of the layer, independent of the spatial distribution of the nonlinearity. On the other hand, the coefficient of reflection is proportional to a weighted average of the nonlinearity across the layer thickness. The weight function in this weighted average is related to the propagating phase, thus making the coefficient of reflection dependent on the spatial distribution of the nonlinearity. Finally, the paper concludes with some discussions on how to use the reflected and transmitted second harmonic waves to evaluate the variance and autocorrelation length of nonlinear parameter β when the nonlinearity distribution in the layer is a stochastic process.
International Nuclear Information System (INIS)
Yim, K.; Wong, R.C.
1995-01-01
Gas mixing phenomena can be modelled using distributed parameter codes such as GOTHIC, but the selection of the optimum cell size is an important user input. The tradeoff between accuracy and practical computation times affect the choice of cell sizes, where small cells provide better accuracy at the expense of longer computing time. A study on cell size effect on hydrogen distribution is presented for the problem of hydrogen mixing behaviour in a typical CANDU reactor containment following a severe reactor accident. Optimal cell sizes were found for different room volumes, hydrogen release profiles and elevations using spatial convergence criteria. The findings of this study provide the technical basis for the cell size selection in the GOTHIC distributed parameter models used for analysing hydrogen mixing behaviour. (author). 1 ref., 1 tab., 13 figs
Directory of Open Access Journals (Sweden)
C. Bandaragoda
2011-05-01
Full Text Available To support the goal of distributed hydrologic and instream model predictions based on physical processes, we explore multi-dimensional parameterization determined by a broad set of observations. We present a systematic approach to using various data types at spatially distributed locations to decrease parameter bounds sampled within calibration algorithms that ultimately provide information regarding the extent of individual processes represented within the model structure. Through the use of a simulation matrix, parameter sets are first locally optimized by fitting the respective data at one or two locations and then the best results are selected to resolve which parameter sets perform best at all locations, or globally. This approach is illustrated using the Two-Zone Temperature and Solute (TZTS model for a case study in the Virgin River, Utah, USA, where temperature and solute tracer data were collected at multiple locations and zones within the river that represent the fate and transport of both heat and solute through the study reach. The result was a narrowed parameter space and increased parameter certainty which, based on our results, would not have been as successful if only single objective algorithms were used. We also found that the global optimum is best defined by multiple spatially distributed local optima, which supports the hypothesis that there is a discrete and narrowly bounded parameter range that represents the processes controlling the dominant hydrologic responses. Further, we illustrate that the optimization process itself can be used to determine which observed responses and locations are most useful for estimating the parameters that result in a global fit to guide future data collection efforts.
Barber, Jared; Tanase, Roxana; Yotov, Ivan
2016-06-01
Several Kalman filter algorithms are presented for data assimilation and parameter estimation for a nonlinear diffusion model of epithelial cell migration. These include the ensemble Kalman filter with Monte Carlo sampling and a stochastic collocation (SC) Kalman filter with structured sampling. Further, two types of noise are considered -uncorrelated noise resulting in one stochastic dimension for each element of the spatial grid and correlated noise parameterized by the Karhunen-Loeve (KL) expansion resulting in one stochastic dimension for each KL term. The efficiency and accuracy of the four methods are investigated for two cases with synthetic data with and without noise, as well as data from a laboratory experiment. While it is observed that all algorithms perform reasonably well in matching the target solution and estimating the diffusion coefficient and the growth rate, it is illustrated that the algorithms that employ SC and KL expansion are computationally more efficient, as they require fewer ensemble members for comparable accuracy. In the case of SC methods, this is due to improved approximation in stochastic space compared to Monte Carlo sampling. In the case of KL methods, the parameterization of the noise results in a stochastic space of smaller dimension. The most efficient method is the one combining SC and KL expansion. Copyright © 2016 Elsevier Inc. All rights reserved.
Partial stabilization and control of distributed parameter systems with elastic elements
Zuyev, Alexander L
2015-01-01
This monograph provides a rigorous treatment of problems related to partial asymptotic stability and controllability for models of flexible structures described by coupled nonlinear ordinary and partial differential equations or equations in abstract spaces. The text is self-contained, beginning with some basic results from the theory of continuous semigroups of operators in Banach spaces. The problem of partial asymptotic stability with respect to a continuous functional is then considered for a class of abstract multivalued systems on a metric space. Next, the results of this study are applied to the study of a rotating body with elastic attachments. Professor Zuyev demonstrates that the equilibrium cannot be made strongly asymptotically stable in the general case, motivating consideration of the problem of partial stabilization with respect to the functional that represents “averaged” oscillations. The book’s focus moves on to spillover analysis for infinite-dimensional systems with finite-dimensio...
Modelling and dynamics analysis of heat exchanger as a distributed parameter process
International Nuclear Information System (INIS)
Savic, B.; Debeljkovic, D.Lj.
2004-01-01
A non-linear and afterwards linearized mathematical model of fuel oil cooling chamber has been developed. This chamber is a part of a recuperative heat exchanger of a tube-in-tube type and of opposite-direction acting, set in a heavy oil fraction discharge tubing. The model is defined as a range of assumptions and simplifications from which energy balance equations under non-stationary operating conditions are derived. The model is in the form of a set of partial differential equations with constant coefficients. Using appropriate numerical simulation of the transfer function, the dynamic of this process has been shown in the form of appropriate transient process responses which quite well correspond to the real process behavior
Modelling and dynamics analysis of heat exchanger as a distributed parameter process
Energy Technology Data Exchange (ETDEWEB)
Savic, B.; Debeljkovic, D.Lj. [University of Belgrade, Department of Control Engineering, Belgrade (Yugoslavia)
2004-07-01
A non-linear and afterwards linearized mathematical model of fuel oil cooling chamber has been developed. This chamber is a part of a recuperative heat exchanger of a tube-in-tube type and of opposite-direction acting, set in a heavy oil fraction discharge tubing. The model is defined as a range of assumptions and simplifications from which energy balance equations under non-stationary operating conditions are derived. The model is in the form of a set of partial differential equations with constant coefficients. Using appropriate numerical simulation of the transfer function, the dynamic of this process has been shown in the form of appropriate transient process responses which quite well correspond to the real process behavior.
Choosing put option parameters based on quantiles from the distribution of portfolio value
Bell, Peter Newton
2014-01-01
This paper explores how a put option changes the probability distribution of portfolio value. The paper extends the model introduced in Bell (2014) by allowing both the quantity and strike price to vary. I use the 5% quantile from the portfolio distribution to measure riskiness and compare different put options. I report a so-called ‘quantile surface’ that shows the quantile across different combinations of quantity and strike price. I find that it is possible to maximize the quantile by ...
Determine the Dose Distribution Using Ultrasound Parameters in MAGIC-f Polymer Gels
Directory of Open Access Journals (Sweden)
Hossein Masoumi
2016-02-01
Full Text Available In this study, using methacrylic and ascorbic acid in gelatin initiated by copper (MAGIC-f polymer gel after megavoltage energy exposure, the sensitivity of the ultrasound velocity and attenuation coefficient dose-dependent parameters was evaluated. The MAGIC-f polymer gel was irradiated under 1.25 MeV cobalt-60, ranging from 0 to 60 Gy in 2-Gy steps, and received dose uniformity and accuracy of ±2%. After calibration of the ultrasonic systems with a frequency of 500 kHz, the parameters of ultrasound velocity and attenuation coefficient of the irradiated gel samples were measured. According to the dose–response curve, the ability of ultrasonic parameters was evaluated in dose rate readings. Based on a 4-order polynomial curve, fitted on the dose–response parameters of ultrasound velocity and attenuation coefficient and observed at 24 hours after irradiation, ultrasonic parameters had more sensitivity. The sensitivity of the dose–velocity and dose-attenuation coefficient curves was observed as 50 m/s/Gy and 0.06 dB/MHz/Gy over the linear range of 4 to 44 Gy, respectively. The ultrasonic parameters at 5°C, 15°C, and 25°C on the gel dosimeter after 0 to 60 Gy irradiation showed that readings at 25°C have higher sensitivity compared to 15°C and 5°C. Maximum sensitivity time and temperature readings of the MAGIC-f ultrasonic parameters were concluded 24 hours after irradiation and at a temperature of 25°C.
Directory of Open Access Journals (Sweden)
C. S. Edmonds
2014-05-01
Full Text Available In high chromaticity circular accelerators, rapid decoherence of the betatron motion of a particle beam can make the measurement of lattice and bunch values, such as Courant-Snyder parameters and betatron amplitude, difficult. A method for reconstructing the momentum distribution of a beam from beam position measurements is presented. Further analysis of the same beam position monitor data allows estimates to be made of the Courant-Snyder parameters and the amplitude of coherent betatron oscillation of the beam. The methods are tested through application to data taken on the linear nonscaling fixed field alternating gradient accelerator, EMMA.
Recommended food chain parameter values and distributions for use around CANDU sites in Ontario
Energy Technology Data Exchange (ETDEWEB)
Peterson, S R
1996-07-01
Site-specific parameter values should be used whenever possible to increase the accuracy of dose predictions. Parameter values specific to agricultural practices and human lifestyles in southern Ontario are presented for use in CSA-N288.1-M87 (Canadian Standards Association Guidelines for Calculating Derived Release Limits for Radioactive Material in Airborne and Liquid Effluents for Normal Operation of Nuclear Facilities) and CHERPAC (Chalk River Environmental Research Pathways Analysis Code). Use of these values in place of the default parameter values in CSA-N288.1-M87 is shown to reduce the predicted dose by nearly a factor of 2. (author). 27 refs., 6 tabs., 1 fig.
Recommended food chain parameter values and distributions for use around CANDU sites in Ontario
International Nuclear Information System (INIS)
Peterson, S.R.
1996-07-01
Site-specific parameter values should be used whenever possible to increase the accuracy of dose predictions. Parameter values specific to agricultural practices and human lifestyles in southern Ontario are presented for use in CSA-N288.1-M87 (Canadian Standards Association Guidelines for Calculating Derived Release Limits for Radioactive Material in Airborne and Liquid Effluents for Normal Operation of Nuclear Facilities) and CHERPAC (Chalk River Environmental Research Pathways Analysis Code). Use of these values in place of the default parameter values in CSA-N288.1-M87 is shown to reduce the predicted dose by nearly a factor of 2. (author). 27 refs., 6 tabs., 1 fig
Syaina, L. P.; Majidi, M. A.
2018-04-01
Single impurity Anderson model describes a system consisting of non-interacting conduction electrons coupled with a localized orbital having strongly interacting electrons at a particular site. This model has been proven successful to explain the phenomenon of metal-insulator transition through Anderson localization. Despite the well-understood behaviors of the model, little has been explored theoretically on how the model properties gradually evolve as functions of hybridization parameter, interaction energy, impurity concentration, and temperature. Here, we propose to do a theoretical study on those aspects of a single impurity Anderson model using the distributional exact diagonalization method. We solve the model Hamiltonian by randomly generating sampling distribution of some conducting electron energy levels with various number of occupying electrons. The resulting eigenvalues and eigenstates are then used to define the local single-particle Green function for each sampled electron energy distribution using Lehmann representation. Later, we extract the corresponding self-energy of each distribution, then average over all the distributions and construct the local Green function of the system to calculate the density of states. We repeat this procedure for various values of those controllable parameters, and discuss our results in connection with the criteria of the occurrence of metal-insulator transition in this system.
Distributed parameter estimation in unreliable sensor networks via broadcast gossip algorithms.
Wang, Huiwei; Liao, Xiaofeng; Wang, Zidong; Huang, Tingwen; Chen, Guo
2016-01-01
In this paper, we present an asynchronous algorithm to estimate the unknown parameter under an unreliable network which allows new sensors to join and old sensors to leave, and can tolerate link failures. Each sensor has access to partially informative measurements when it is awakened. In addition, the proposed algorithm can avoid the interference among messages and effectively reduce the accumulated measurement and quantization errors. Based on the theory of stochastic approximation, we prove that our proposed algorithm almost surely converges to the unknown parameter. Finally, we present a numerical example to assess the performance and the communication cost of the algorithm. Copyright © 2015 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Paul, D. [SSBB and Senior Member-ASQ, Kolkata (India); Mandal, S.N. [Kalyani Govt Engg College, Kalyani (India); Mukherjee, D.; Bhadra Chaudhuri, S.R. [Dept of E. and T. C. Engg, B.E.S.U., Shibpur (India)
2010-10-15
System efficiency and payback time are yet to attain a commercially viable level for solar photovoltaic energy projects. Despite huge development in prediction of solar radiation data, there is a gap in extraction of pertinent information from such data. Hence the available data cannot be effectively utilized for engineering application. This is acting as a barrier for the emerging technology. For making accurate engineering and financial calculations regarding any solar energy project, it is crucial to identify and optimize the most significant statistic(s) representing insolation availability by the Photovoltaic setup at the installation site. Quality Function Deployment (QFD) technique has been applied for identifying the statistic(s), which are of high significance from a project designer's point of view. A MATLAB trademark program has been used to build the annual frequency distribution of hourly insolation over any module plane at a given location. Descriptive statistical analysis of such distributions is done through MINITAB trademark. For Building Integrated Photo Voltaic (BIPV) installation, similar statistical analysis has been carried out for the composite frequency distribution, which is formed by weighted summation of insolation distributions for different module planes used in the installation. Vital most influential statistic(s) of the composite distribution have been optimized through Artificial Neural Network computation. This approach is expected to open up a new horizon in BIPV system design. (author)
Parameter Recovery for the 1-P HGLLM with Non-Normally Distributed Level-3 Residuals
Kara, Yusuf; Kamata, Akihito
2017-01-01
A multilevel Rasch model using a hierarchical generalized linear model is one approach to multilevel item response theory (IRT) modeling and is referred to as a one-parameter hierarchical generalized linear logistic model (1-P HGLLM). Although it has the flexibility to model nested structure of data with covariates, the model assumes the normality…
Optimal Configuration of Fault-Tolerance Parameters for Distributed Server Access
DEFF Research Database (Denmark)
Daidone, Alessandro; Renier, Thibault; Bondavalli, Andrea
2013-01-01
Server replication is a common fault-tolerance strategy to improve transaction dependability for services in communications networks. In distributed architectures, fault-diagnosis and recovery are implemented via the interaction of the server replicas with the clients and other entities...... model using stochastic activity networks (SAN) for the evaluation of performance and dependability metrics of a generic transaction-based service implemented on a distributed replication architecture. The composite SAN model can be easily adapted to a wide range of client-server applications deployed...
Effect of process parameters on temperature distribution in twin-electrode TIG coupling arc
Zhang, Guangjun; Xiong, Jun; Gao, Hongming; Wu, Lin
2012-10-01
The twin-electrode TIG coupling arc is a new type of welding heat source, which is generated in a single welding torch that has two tungsten electrodes insulated from each other. This paper aims at determining the distribution of temperature for the coupling arc using the Fowler-Milne method under the assumption of local thermodynamic equilibrium. The influences of welding current, arc length, and distance between both electrode tips on temperature distribution of the coupling arc were analyzed. Based on the results, a better understanding of the twin-electrode TIG welding process was obtained.
Zakharov, Alexander
It is well-known that one can evaluate black hole (BH) parameters (including spin) analyz-ing trajectories of stars around BH. A bulk distribution of matter (dark matter (DM)+stellar cluster) inside stellar orbits modifies trajectories of stars, namely, generally there is a apoas-tron shift in direction which opposite to GR one, even now one could put constraints on DM distribution and BH parameters and constraints will more stringent in the future. Therefore, an analyze of bright star trajectories provides a relativistic test in a weak gravitational field approximation, but in the future one can test a strong gravitational field near the BH at the Galactic Center with the same technique due to a rapid progress in observational facilities. References A. Zakharov et al., Phys. Rev. D76, 062001 (2007). A.F. Zakharov et al., Space Sci. Rev. 148, 301313(2009).
International Nuclear Information System (INIS)
Kiguchi, T.; Kawai, T.
1975-01-01
A method has been developed to optimally and automatically determine the adjustable parameters of the boiling water reactor three-dimensional core simulator FLARE. The steepest gradient method is adopted for the optimization. The parameters are adjusted to best fit the operating data on power distribution measured by traversing in-core probes (TIP). The average error in the calculated TIP readings normalized by the core average is 0.053 at the rated power. The k-infinity correction term has also been derived theoretically to reduce the relatively large error in the calculated TIP readings near the tips of control rods, which is induced by the coarseness of mesh points. By introducing this correction, the average error decreases to 0.047. The void-quality relation is recognized as a function of coolant flow rate. The relation is estimated to fit the measured distributions of TIP reading at the partial power states
Directory of Open Access Journals (Sweden)
Jong-Wuu Wu
2013-01-01
Full Text Available We propose the weighted moments estimators (WMEs of the location and scale parameters for the extreme value distribution based on the multiply type II censored sample. Simulated mean squared errors (MSEs of best linear unbiased estimator (BLUE and exact MSEs of WMEs are compared to study the behavior of different estimation methods. The results show the best estimator among the WMEs and BLUE under different combinations of censoring schemes.
Radar meteors range distribution model. III. Ablation, shape-density and self-similarity parameters
Czech Academy of Sciences Publication Activity Database
Pecinová, Drahomíra; Pecina, Petr
2007-01-01
Roč. 37, č. 3 (2007), s. 147-160 ISSN 1335-1842 R&D Projects: GA ČR GA205/03/1405 Institutional research plan: CEZ:AV0Z10030501 Keywords : physics of meteors * radar meteors * range distribution Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics
Robustness of parameter-less remote real-time pressure control in water distribution systems
CSIR Research Space (South Africa)
Page, Philip R
2017-06-01
Full Text Available One way of reducing water leakage, pipe bursts and water consumption in a water distribution system (WDS) is to manage the pressure to be as low as possible. This can be done by adjusting a pressure control valve (PCV) in real-time in order to keep...